Skip to content

(City,Zip) pair Match #29

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
zmousavi wants to merge 2 commits into
base: master
Choose a base branch
from
Open

(City,Zip) pair Match #29

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
4465f51
check for (city, zip) match implemented
zmousavi Aug 18, 2020
22436a4
removed unused library
zmousavi Aug 18, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 25 additions & 9 deletions code/data_dictionary.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ library(lubridate)
library(knitr)
library(stringdist) # for fuzzy matching
library(tidyr)

# Summaries ---------------------------------------------------------------

glimpse(adbs)
Expand Down Expand Up @@ -102,20 +103,20 @@ zip_demo <- read.csv("data/demographics/zipcodeDemographics.csv")
validzips_ztzfile_only = adbs$Zip[(adbs$Zip %in% sprintf("%05d", ztz$ZIP_CODE)) & !(adbs$Zip %in% sprintf("%05d", uszips$zip))]
validzipsfromztz_hasdemo = sum(validzips_ztzfile_only %in% sprintf("%05d", zip_demo$GEOID))

cat(sprintf('%s unique ppp zips are listed in zip_to_zcta file that are not in the uszips file,
covering %s rows in ppp file. However, %s of these zipcode are in the demo file.',
cat(sprintf('%s unique ppp zips are listed in zip_to_zcta file that are not in the uszips file,
covering %s rows in ppp file. However, %s of these zipcode are in the demo file.\n',
length(unique(validzips_ztzfile_only)) , length(validzips_ztzfile_only), validzipsfromztz_hasdemo))

validzips_uscitiesfile_only = adbs$Zip[(adbs$Zip %in% sprintf("%05d", uscities_expanded$zips)) & !(adbs$Zip %in% sprintf("%05d", uszips$zip))]
validzipfromcity_hasdemo = sum(validzips_uscitiesfile_only %in% sprintf("%05d", zip_demo$GEOID))

cat(sprintf('%s unique ppp zips are listed in uscities_zips file that are not in the uszips file,
covering %s rows in ppp file. However, %s of these zipcode are in the demo file.',
cat(sprintf('%s unique ppp zips are listed in uscities_zips file that are not in the uszips file,
covering %s rows in ppp file. However, %s of these zipcode are in the demo file.\n',
length(unique(validzips_uscitiesfile_only)) , length(validzips_uscitiesfile_only), validzipfromcity_hasdemo))

#Add a Valid column and a hasdemo column:
adbs$ValidZip = adbs$ValidZip_uszips | adbs$ValidZip_ztz | adbs$ValidZip_uscities
table(adbs$ValidZip, useNA = "always")
table(adbs$ValidZip, useNA = "always")

#hasdemo is essentiall column, but actually creating for correctness:
adbs <- adbs %>% mutate(ValidZip_hasdemo = case_when(
Expand Down Expand Up @@ -151,7 +152,7 @@ imputed_states = c()
imputed_states2 = c()
missing_zips = c()
for (zip in XXstate_zip){

state = uszips[uszips$zip==zip,]$state_id

if (identical(state, character(0))){
Expand All @@ -170,7 +171,7 @@ cat(sprintf("out of the %s missing states that had zip entry, %s states imputed

### Data Check: City Names -------------------------------------------------
# check City values against a large list of likely names, via: https://simplemaps.com/data/us-cities

#
citydict <- sort(unique(tolower(gsub("[[:digit:][:space:][:punct:]]", "", uscities$city))))
adbscities <- sort(unique(tolower(gsub("[[:digit:][:space:][:punct:]]", "", adbs$City))))

Expand Down Expand Up @@ -206,13 +207,28 @@ adbs <- adbs %>% mutate(ValidCity = case_when(

table(adbs$ValidCity, useNA = "always")

adbs$City_edited = (tolower(gsub("[[:digit:][:space:][:punct:]]", "" , str_replace(tolower(adbs$City), "saint", "st"))))
adbs_validcities = unique(adbs[adbs$ValidCity == 'True' , ]$City_edited)
cat(sprintf('There are %d unique valid cities', length(adbs_validcities)))


#Data Validation: (City, Zip) match --------------------------------------------------------------
#From the Quartz article: The zipcode listed for a loan in ... San Diege has the zipcode of Pasadena.
#From the Quartz article: The zipcode listed for a loan in ... San Diego has the zipcode of Pasadena.
#Are there more entries with mismatches between (City, Zip)?
#Reference used is "./data/simplemaps_uscities_basicv1.6/uscities.csv"

#Check to see that all setdiff(uscities$zips, uszips$zip) = 0
#Check to see that all setdiff(uscities$zips, uszips$zip) = 0
#Get the zipcode associated with cities listed in the ppp file
uscities_expanded$city_edited = (tolower(gsub("[[:digit:][:space:][:punct:]]", "", uscities_expanded$city)))

valid_city_zips = sprintf("%s_%s", uscities_expanded$city_edited, uscities_expanded$zips)
adbs_city_zip = sprintf("%s_%s", adbs$City_edited, adbs$Zip)
adbs$CityZip_match = NA
adbs$CityZip_match = adbs_city_zip %in% valid_city_zips

table(adbs$CityZip_match, useNA = "always")
#3880594 (City, Zip) match.
#1004794 do not have matching (City, Zip) or have inavlid Zip and/or City entries


### Data Check: Jobs Retained ----------------------------------------------
Expand Down