diff --git a/allData_myVersion.csv b/allData_myVersion.csv
new file mode 100644
index 0000000..1789441
--- /dev/null
+++ b/allData_myVersion.csv
@@ -0,0 +1,39889 @@
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diff --git a/analysis.R b/analysis.R
new file mode 100644
index 0000000..89af496
--- /dev/null
+++ b/analysis.R
@@ -0,0 +1,101 @@
+# Introduction to Biocomputing - R Project
+# Written by Xiyuan Guan
+# 2022-12-1
+# analysis
+library(ggplot2)
+
+setwd("C:/Users/guanx/Documents/N.ND/BIOS 60318 Biocomputing/test/Rproject/Rproject/")
+source("supportingFunctions.R")
+
+# converts all .txt files in "countryY" into .csv format.####
+trans.csv("countryY"," ")
+
+
+# compile data from all .csv files in "countryX" and "countryY"
+sumtable1 <- combine.csv("countryX","Warn")
+sumtable2 <- combine.csv("countryY","Warn")
+# compile all data
+allcsv <- rbind(sumtable1,sumtable2)
+write.csv(allcsv,"allData_myVersion.csv", row.names = F)
+
+# summarize the compiled data set
+file <- read.csv("allData.csv")
+sub.pat <- sumdata(file) # this step takes time
+# the summary of the age distribution of patients is shown in console. 
+write.csv(sub.pat,"subset_of_patients.csv",row.names = F) # for better load
+
+# beginning of answers####
+
+# Q1: In which country (X or Y) did the disease outbreak likely begin?####
+# generate dataset with day, number of patients and country
+day_num <- data.frame(matrix(NA,0,3))
+colnames(day_num) <- c("dayofYear","num_patient","country")
+Xdays<- unique(file$dayofYear[which(file$country=="X")]) # days with patients in X country
+Ydays <- unique(file$dayofYear[which(file$country=="Y")])
+setdiff(Xdays,Ydays) # same
+for(i in 1:length(Xdays)){
+  day_num[i,1] <- Xdays[i] # dayofYear
+  XPat <- file[which(file$dayofYear==Xdays[i]&file$country=="X"),]# subset country and day
+  nXPat<- XPat[which(rowSums(XPat[,3:12])>0),] # subset patients
+  day_num[i,2] <- nrow(nXPat) # num of patient
+  day_num[i,3] <- "X"
+}
+nrow(day_num) #56
+for(i in 1:length(Ydays)){
+  day_num[i+56,1] <- Ydays[i] # dayofYear
+  YPat <- file[which(file$dayofYear==Ydays[i]&file$country=="Y"),] # subset country and day
+  nYPat<- YPat[which(rowSums(YPat[,3:12])>0),] # subset patients
+  day_num[i+56,2] <- nrow(nYPat) # num of patient
+  day_num[i+56,3] <- "Y"
+}
+
+head(day_num)
+
+# sum(day_num[,2]) # test data accuracy = nrow(sub.pat)
+
+# save as plot_1.png
+ggplot(data=day_num, aes(x = dayofYear, y = num_patient, group = country, color = country, shape = country))+
+  geom_line(linewidth = 0.1)+
+  geom_point()+
+  theme_bw()
+  
+# accumulated num of patient could be better
+# generate dataset with day, accumulated number of patients, country
+day_num$acc_num[1:56] <- cumsum(day_num$num_patient[1:56]) # 
+day_num$acc_num[57:112] <- cumsum(day_num$num_patient[57:112]) #Y
+
+# save as plot_2.png
+ggplot(data=day_num, aes(x = dayofYear, y = acc_num, group = country, color = country, shape = country))+
+  geom_line(linewidth = 0.5)+
+  geom_point(size=1)+
+  theme_bw()
+
+# A1: According to plot_1 and plot_2, the disease started to break in country X before the 120th day of the year,
+# which is the start day of screening. However, the disease started to break in country y on around the 139th day
+# of the year, so the disease outbreak likely begin in country X.
+
+# Q2: If Country Y develops a vaccine for the disease, is it likely to work for citizens of Country X?####
+
+mark_num <- data.frame(matrix(NA,20,3))
+colnames(mark_num) <- c("marker","num_of_patient","country")
+mark_num[,1] <- rep(colnames(file[,3:12]),2) # 10 markers
+mark_num[1:10,3] <- "X"
+mark_num[11:20,3] <- "Y"
+for(i in 3:12){
+  mark_num[i-2,2] <- sum(file[which(file$country=="X"),i])
+  mark_num[i+8,2] <- sum(file[which(file$country=="Y"),i])
+}
+
+#generate plot_3
+ggplot(data = mark_num, aes(x = marker, y = num_of_patient, fill = country))+
+  geom_bar(stat = "identity", position = "dodge")+
+  theme(axis.text.x = element_text(angle = 60, hjust = 1))+
+  scale_y_continuous(expand = c(0,0))+
+  xlab("")
+
+# A2: According to plot_3, in country X, marker01-05 are mainly present in patients' sample,
+# while in country Y, marker04-10 are mainly present, which indicates different proteins
+# shown to form the immunological response by the patients, so indicates differences in the 
+# protein in the disease. So the vaccine developed by Country Y may work on the strain that
+# has marker04-10 as the response to disease-causing agents, and may not work on the strain 
+# in Country X with marker01-05 as the response.
\ No newline at end of file
diff --git a/countryY/screen_120.csv b/countryY/screen_120.csv
index 1d6083f..127128d 100644
--- a/countryY/screen_120.csv
+++ b/countryY/screen_120.csv
@@ -1,498 +1,498 @@
-"gender","age","marker01","marker02","marker03","marker04","marker05","marker06","marker07","marker08","marker09","marker10"
-"female",14,0,0,0,0,0,0,0,0,0,0
-"male",41,0,0,0,0,0,0,0,0,0,0
-"female",11,0,0,0,0,0,0,0,0,0,0
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-"female",21,0,0,0,0,0,0,0,0,0,0
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diff --git a/countryY/screen_121.csv b/countryY/screen_121.csv
index 7b3f944..d0dfb81 100644
--- a/countryY/screen_121.csv
+++ b/countryY/screen_121.csv
@@ -1,485 +1,485 @@
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diff --git a/countryY/screen_122.csv b/countryY/screen_122.csv
index a415351..7e6db70 100644
--- a/countryY/screen_122.csv
+++ b/countryY/screen_122.csv
@@ -1,480 +1,480 @@
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diff --git a/countryY/screen_123.csv b/countryY/screen_123.csv
index 1aa0849..7eeefe0 100644
--- a/countryY/screen_123.csv
+++ b/countryY/screen_123.csv
@@ -1,253 +1,253 @@
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diff --git a/countryY/screen_124.csv b/countryY/screen_124.csv
index 8ada20c..a5a990f 100644
--- a/countryY/screen_124.csv
+++ b/countryY/screen_124.csv
@@ -1,480 +1,480 @@
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diff --git a/countryY/screen_125.csv b/countryY/screen_125.csv
index f57e772..00435f7 100644
--- a/countryY/screen_125.csv
+++ b/countryY/screen_125.csv
@@ -1,251 +1,251 @@
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diff --git a/countryY/screen_126.csv b/countryY/screen_126.csv
index fb7c0dd..2b33191 100644
--- a/countryY/screen_126.csv
+++ b/countryY/screen_126.csv
@@ -1,288 +1,288 @@
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diff --git a/countryY/screen_127.csv b/countryY/screen_127.csv
index 77ce93f..33fc4c7 100644
--- a/countryY/screen_127.csv
+++ b/countryY/screen_127.csv
@@ -1,250 +1,250 @@
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diff --git a/countryY/screen_128.csv b/countryY/screen_128.csv
index 3616248..af8da84 100644
--- a/countryY/screen_128.csv
+++ b/countryY/screen_128.csv
@@ -1,360 +1,360 @@
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diff --git a/countryY/screen_129.csv b/countryY/screen_129.csv
index bac88c7..7e37f6a 100644
--- a/countryY/screen_129.csv
+++ b/countryY/screen_129.csv
@@ -1,252 +1,252 @@
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diff --git a/countryY/screen_130.csv b/countryY/screen_130.csv
index b40e16e..90014a1 100644
--- a/countryY/screen_130.csv
+++ b/countryY/screen_130.csv
@@ -1,222 +1,222 @@
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diff --git a/countryY/screen_131.csv b/countryY/screen_131.csv
index 1a5f3be..6701d87 100644
--- a/countryY/screen_131.csv
+++ b/countryY/screen_131.csv
@@ -1,225 +1,225 @@
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diff --git a/countryY/screen_132.csv b/countryY/screen_132.csv
index bb3557f..7137c74 100644
--- a/countryY/screen_132.csv
+++ b/countryY/screen_132.csv
@@ -1,241 +1,241 @@
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diff --git a/countryY/screen_133.csv b/countryY/screen_133.csv
index b23d6a1..b2ad49b 100644
--- a/countryY/screen_133.csv
+++ b/countryY/screen_133.csv
@@ -1,276 +1,276 @@
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diff --git a/countryY/screen_134.csv b/countryY/screen_134.csv
index 1160ab4..30cff1f 100644
--- a/countryY/screen_134.csv
+++ b/countryY/screen_134.csv
@@ -1,225 +1,225 @@
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diff --git a/countryY/screen_135.csv b/countryY/screen_135.csv
index a6caab9..69a8f68 100644
--- a/countryY/screen_135.csv
+++ b/countryY/screen_135.csv
@@ -1,398 +1,398 @@
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diff --git a/countryY/screen_136.csv b/countryY/screen_136.csv
index 113e940..fdc383b 100644
--- a/countryY/screen_136.csv
+++ b/countryY/screen_136.csv
@@ -1,469 +1,469 @@
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diff --git a/countryY/screen_137.csv b/countryY/screen_137.csv
index 710dbdc..9d3c475 100644
--- a/countryY/screen_137.csv
+++ b/countryY/screen_137.csv
@@ -1,302 +1,302 @@
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diff --git a/countryY/screen_138.csv b/countryY/screen_138.csv
index 6dea3cf..4975ee9 100644
--- a/countryY/screen_138.csv
+++ b/countryY/screen_138.csv
@@ -1,463 +1,463 @@
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diff --git a/countryY/screen_139.csv b/countryY/screen_139.csv
index fcd21df..9b71adb 100644
--- a/countryY/screen_139.csv
+++ b/countryY/screen_139.csv
@@ -1,378 +1,378 @@
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diff --git a/countryY/screen_140.csv b/countryY/screen_140.csv
index 9278d7a..b885a96 100644
--- a/countryY/screen_140.csv
+++ b/countryY/screen_140.csv
@@ -1,418 +1,418 @@
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diff --git a/countryY/screen_141.csv b/countryY/screen_141.csv
index 9fc8c65..4cc3d0c 100644
--- a/countryY/screen_141.csv
+++ b/countryY/screen_141.csv
@@ -1,452 +1,452 @@
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diff --git a/countryY/screen_142.csv b/countryY/screen_142.csv
index 3aa1f73..c5e9716 100644
--- a/countryY/screen_142.csv
+++ b/countryY/screen_142.csv
@@ -1,434 +1,434 @@
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diff --git a/countryY/screen_143.csv b/countryY/screen_143.csv
index 92555e8..0becc2b 100644
--- a/countryY/screen_143.csv
+++ b/countryY/screen_143.csv
@@ -1,314 +1,314 @@
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diff --git a/countryY/screen_144.csv b/countryY/screen_144.csv
index af9623a..92ac7fb 100644
--- a/countryY/screen_144.csv
+++ b/countryY/screen_144.csv
@@ -1,217 +1,217 @@
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diff --git a/countryY/screen_145.csv b/countryY/screen_145.csv
index 603c2bf..8b2ddc0 100644
--- a/countryY/screen_145.csv
+++ b/countryY/screen_145.csv
@@ -1,260 +1,260 @@
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diff --git a/countryY/screen_146.csv b/countryY/screen_146.csv
index 04e80fe..50058e3 100644
--- a/countryY/screen_146.csv
+++ b/countryY/screen_146.csv
@@ -1,448 +1,448 @@
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diff --git a/countryY/screen_147.csv b/countryY/screen_147.csv
index 502c993..850d1f8 100644
--- a/countryY/screen_147.csv
+++ b/countryY/screen_147.csv
@@ -1,326 +1,326 @@
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diff --git a/countryY/screen_148.csv b/countryY/screen_148.csv
index 8175ed6..fe3573b 100644
--- a/countryY/screen_148.csv
+++ b/countryY/screen_148.csv
@@ -1,368 +1,368 @@
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diff --git a/countryY/screen_149.csv b/countryY/screen_149.csv
index 0197e79..e504254 100644
--- a/countryY/screen_149.csv
+++ b/countryY/screen_149.csv
@@ -1,251 +1,251 @@
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diff --git a/countryY/screen_150.csv b/countryY/screen_150.csv
index bd01a9c..39919f2 100644
--- a/countryY/screen_150.csv
+++ b/countryY/screen_150.csv
@@ -1,297 +1,297 @@
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diff --git a/countryY/screen_151.csv b/countryY/screen_151.csv
index e2e4b6c..6842d05 100644
--- a/countryY/screen_151.csv
+++ b/countryY/screen_151.csv
@@ -1,330 +1,330 @@
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diff --git a/countryY/screen_152.csv b/countryY/screen_152.csv
index 0b4833a..858d0dc 100644
--- a/countryY/screen_152.csv
+++ b/countryY/screen_152.csv
@@ -1,389 +1,389 @@
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diff --git a/countryY/screen_153.csv b/countryY/screen_153.csv
index 136acf1..f58ec0a 100644
--- a/countryY/screen_153.csv
+++ b/countryY/screen_153.csv
@@ -1,477 +1,477 @@
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diff --git a/countryY/screen_154.csv b/countryY/screen_154.csv
index ca0241d..7bb44e4 100644
--- a/countryY/screen_154.csv
+++ b/countryY/screen_154.csv
@@ -1,272 +1,272 @@
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diff --git a/countryY/screen_155.csv b/countryY/screen_155.csv
index 83a23fe..68dd47d 100644
--- a/countryY/screen_155.csv
+++ b/countryY/screen_155.csv
@@ -1,420 +1,420 @@
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diff --git a/countryY/screen_156.csv b/countryY/screen_156.csv
index a7bbad2..1035717 100644
--- a/countryY/screen_156.csv
+++ b/countryY/screen_156.csv
@@ -1,369 +1,369 @@
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diff --git a/countryY/screen_157.csv b/countryY/screen_157.csv
index ab9c91f..cfa6202 100644
--- a/countryY/screen_157.csv
+++ b/countryY/screen_157.csv
@@ -1,269 +1,269 @@
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diff --git a/countryY/screen_158.csv b/countryY/screen_158.csv
index a722190..adb7df1 100644
--- a/countryY/screen_158.csv
+++ b/countryY/screen_158.csv
@@ -1,370 +1,370 @@
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diff --git a/countryY/screen_159.csv b/countryY/screen_159.csv
index a94d5ad..f492fe5 100644
--- a/countryY/screen_159.csv
+++ b/countryY/screen_159.csv
@@ -1,468 +1,468 @@
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diff --git a/countryY/screen_160.csv b/countryY/screen_160.csv
index 42dce4b..4c4281d 100644
--- a/countryY/screen_160.csv
+++ b/countryY/screen_160.csv
@@ -1,480 +1,480 @@
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diff --git a/countryY/screen_161.csv b/countryY/screen_161.csv
index 3436247..8f55c61 100644
--- a/countryY/screen_161.csv
+++ b/countryY/screen_161.csv
@@ -1,309 +1,309 @@
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diff --git a/countryY/screen_162.csv b/countryY/screen_162.csv
index 64c52db..a55e1cc 100644
--- a/countryY/screen_162.csv
+++ b/countryY/screen_162.csv
@@ -1,435 +1,435 @@
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diff --git a/countryY/screen_163.csv b/countryY/screen_163.csv
index edfe02d..00e6d8c 100644
--- a/countryY/screen_163.csv
+++ b/countryY/screen_163.csv
@@ -1,248 +1,248 @@
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diff --git a/countryY/screen_164.csv b/countryY/screen_164.csv
index 8b3e70d..d346629 100644
--- a/countryY/screen_164.csv
+++ b/countryY/screen_164.csv
@@ -1,302 +1,302 @@
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diff --git a/countryY/screen_165.csv b/countryY/screen_165.csv
index 92112ac..a1ebc78 100644
--- a/countryY/screen_165.csv
+++ b/countryY/screen_165.csv
@@ -1,309 +1,309 @@
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diff --git a/countryY/screen_166.csv b/countryY/screen_166.csv
index 10b6ffe..d8a7d60 100644
--- a/countryY/screen_166.csv
+++ b/countryY/screen_166.csv
@@ -1,349 +1,349 @@
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diff --git a/countryY/screen_167.csv b/countryY/screen_167.csv
index 07772dc..d62b125 100644
--- a/countryY/screen_167.csv
+++ b/countryY/screen_167.csv
@@ -1,489 +1,489 @@
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diff --git a/countryY/screen_168.csv b/countryY/screen_168.csv
index 4c33754..df463fe 100644
--- a/countryY/screen_168.csv
+++ b/countryY/screen_168.csv
@@ -1,498 +1,498 @@
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diff --git a/countryY/screen_169.csv b/countryY/screen_169.csv
index b89d421..9842de2 100644
--- a/countryY/screen_169.csv
+++ b/countryY/screen_169.csv
@@ -1,241 +1,241 @@
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diff --git a/countryY/screen_170.csv b/countryY/screen_170.csv
index 5b057d0..8b7b0af 100644
--- a/countryY/screen_170.csv
+++ b/countryY/screen_170.csv
@@ -1,443 +1,443 @@
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diff --git a/countryY/screen_171.csv b/countryY/screen_171.csv
index 04dbd5d..c3ff734 100644
--- a/countryY/screen_171.csv
+++ b/countryY/screen_171.csv
@@ -1,451 +1,451 @@
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diff --git a/countryY/screen_172.csv b/countryY/screen_172.csv
index cdb4453..e6f3e7d 100644
--- a/countryY/screen_172.csv
+++ b/countryY/screen_172.csv
@@ -1,331 +1,331 @@
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diff --git a/countryY/screen_173.csv b/countryY/screen_173.csv
index 704eaa1..69ee16b 100644
--- a/countryY/screen_173.csv
+++ b/countryY/screen_173.csv
@@ -1,298 +1,298 @@
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diff --git a/countryY/screen_174.csv b/countryY/screen_174.csv
index c1cd2ef..286ac16 100644
--- a/countryY/screen_174.csv
+++ b/countryY/screen_174.csv
@@ -1,390 +1,390 @@
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diff --git a/countryY/screen_175.csv b/countryY/screen_175.csv
index 9d00a50..5301fc3 100644
--- a/countryY/screen_175.csv
+++ b/countryY/screen_175.csv
@@ -1,364 +1,364 @@
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diff --git a/plot_1_num_of_patient_day.png b/plot_1_num_of_patient_day.png
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diff --git a/plot_2_accum_patient_day.png b/plot_2_accum_patient_day.png
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diff --git a/plot_3_num_patient_marker.png b/plot_3_num_patient_marker.png
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diff --git a/supportingFunctions.R b/supportingFunctions.R
new file mode 100644
index 0000000..35969b7
--- /dev/null
+++ b/supportingFunctions.R
@@ -0,0 +1,99 @@
+# Introduction to Biocomputing - R Project
+# Written by Xiyuan Guan
+# 2022-12-2
+# Supporting Functions
+
+workpath <- "C:/Users/guanx/Documents/N.ND/BIOS 60318 Biocomputing/test/Rproject/Rproject/"
+setwd(workpath)
+list.files()
+
+
+# Write a function that converts all files in a directory with space- or tab-delimited data (.txt) into comma-separated value files.
+# Usage: trans.csv($1,$2), $1 is the directory that contains the files to be transfered into csv format.
+# $2 is the separation in txt files.
+# Example: trans.csv("countryY"," ")
+trans.csv <- function(direct, sepf){
+  #list.files(direct) 
+  files <- list.files(direct,pattern = ".txt") # get all .txt files
+  for(i in 1:length(files)){
+    f <- paste(direct,files[i], sep = "/") # generate file path
+    csvf <- read.table(file = f, sep = sepf, header = T)
+    csvname <- paste(direct,gsub("txt","csv",files[i]),sep = "/") # generate output file path
+    write.csv(csvf, file = csvname, row.names = F)
+  }
+}
+
+
+# Write a function to compile data from all .csv files in a directory into a single .csv file.
+# The user should be able to choose whether they want to remove rows with NA’s in any columns, 
+# include NAs in the compiled data but be warned of their presence, 
+# or include NAs in the compiled data without a warning
+
+# Usage: combine.csv($1,$2), $1 is the directory that contains the files to be combined.
+# $2 is the treatment of NA, could be choose from Delete (delete rows with NA), Warn (include NAs but warn) and NoWarn (include NAs w/o warn).
+# Example: sumtable1 <- combine.csv("countryY","Warn")
+
+combine.csv <- function(direct, NAWarn){
+  files <- list.files(direct,pattern = ".csv") # get all .csv files in the directory
+  cFile <- data.frame(matrix(NA,0,14)) # normalize the data.frame
+  
+  for(i in 1:length(files)){
+    f <- paste(direct,files[i], sep = "/") # get file path
+    csvf <- read.csv(f)
+    country <- gsub("country","",direct)
+    day <- gsub("[^0-9]","",files[i]) # get the number in the file name
+    csvf <- cbind(csvf,country,day) # generate extra columns
+    colnames(csvf)[13] <- "country"
+    colnames(csvf)[14] <- "dayofYear"
+    cFile <- rbind(cFile, csvf) 
+  }
+  nNAs<- sum(is.na(cFile)) # num of NAs in the compiled dataset
+  if(NAWarn == "Delete"){
+    if(nNAs>0){
+      cFile <- na.omit(cFile)
+      print("rows with NA are removed")
+    }
+  }else if(NAWarn == "Warn"){
+    if(nNAs>0){
+      print("Warning, NAs in the dataset.")
+    }else{
+      print("No NAs in the dataset")
+    }
+  }else if(NAWarn != "Delete"&NAWarn != "NoWarn"&NAWarn != "Warn"){
+    # Increase Robustness
+    print("Wrong input for the second variable")
+  }
+  return(cFile) # return the complied data of the directory
+}
+
+# Write a function to summarize the compiled data set
+# Usage: subset <- sumdata(file)
+# Example: file <- read.csv("allData.csv")
+# sub.pat <- sumdata("allData.csv")
+
+sumdata <- function(file){
+  # number of screens run
+  
+  print("The number of screens run is:")
+  print(nrow(file))
+  
+  sub.pat <- data.frame(matrix(NA,0,14))
+  for(i in 1:nrow(file)){
+    if(sum(file[i,3:12])>0){
+      sub.pat <- rbind(sub.pat, file[i,]) # generate subset of patients
+    }
+  }
+  # percent of patients screened that were infected
+  print("Percent of patients screened that were infected is:")
+  p1 <- nrow(sub.pat)/nrow(file)
+  print(p1)
+  # male vs. female patients
+  print("Percent of male vs. female patients is:")
+  p2 <- nrow(sub.pat[which(sub.pat$gender=="male"),])/nrow(sub.pat[which(sub.pat$gender=="female"),])
+  print(p2)
+  # the age distribution of patients
+  print("the age distribution of patients is:")
+  print(summary(sub.pat$age))
+  # ????? 423 yrs old patient
+  return(sub.pat) # return the subset of patients
+}