diff --git a/.RData b/.RData
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diff --git a/.Rhistory b/.Rhistory
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+infected <- subset(all,all[3:12],0)
+numinfected <-nrow(infected)
+print(numinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+print(numscreen)
+infected <- subset(all,all[3:12] >0)
+numinfected <-nrow(infected)
+print(numinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+print(numscreen)
+infected <- subset(all,all[3:12] >0)
+numinfected <- nrow(infected)
+print(numinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+print(numscreen)
+infected <- subset(all,all[3:12]==0)
+numinfected <- nrow(infected)
+print(numinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+print(numscreen)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+print(numinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+print(numscreen)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+percentinfected = numinfected/numscreen
+print(numinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+print(numscreen)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+percentinfected = numinfected/numscreen
+print(numinfected)
+print(percentinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+maleinfected <- infected["male"].value_counts()
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+print(maleinfected)
+percentinfected = numinfected/numscreen
+print(numinfected)
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+maleinfected <- infected["male"].value_counts()
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+maleinfected <- infected["male"].value_counts
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+maleinfected <- subset(infected, gender == "male")
+nummaleinfected = nrow(maleinfected)
+percentinfected = numinfected/numscreen
+femaleinfected <- subset(infected, gender == "female")
+numfemaleinfected = nrow(femaleinfected)
+print(numfemaleinfected)
+print(nummaleinfected)
+print(numinfected)
+}
+summarizeData("allData.csv")
+#Initialize ggplot2
+library(ggplot2)
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+maleinfected <- subset(infected, gender == "male")
+nummaleinfected = nrow(maleinfected)
+percentinfected = numinfected/numscreen
+femaleinfected <- subset(infected, gender == "female")
+numfemaleinfected = nrow(femaleinfected)
+print(numfemaleinfected)
+print(nummaleinfected)
+print(numinfected)
+ggplot() + geom_histogram(data=infected, aes(x=age,color="red")) +theme_classic()
+}
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+maleinfected <- subset(infected, gender == "male")
+nummaleinfected = nrow(maleinfected)
+percentinfected = numinfected/numscreen
+femaleinfected <- subset(infected, gender == "female")
+numfemaleinfected = nrow(femaleinfected)
+print(numfemaleinfected)
+print(nummaleinfected)
+print(numinfected)
+ggplot() + geom_histogram(data=infected, aes(x=age,color="red")) +theme_classic()
+}
+summarizeData("allData.csv")
+summarizeData<- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+numscreen <- nrow(all)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+maleinfected <- subset(infected, gender == "male")
+nummaleinfected = nrow(maleinfected)
+percentinfected = numinfected/numscreen
+femaleinfected <- subset(infected, gender == "female")
+numfemaleinfected = nrow(femaleinfected)
+print(numfemaleinfected)
+print(nummaleinfected)
+print(numinfected)
+ggplot() + geom_histogram(data=infected, aes(x=age,color="red"), binwidth = 1) +theme_classic()
+}
+summarizeData("allData.csv")
+source(supportingFunctions.R)
+#Initialize ggplot2
+library(ggplot2)
+#Set Working Directory
+setwd("/Users/elias/Downloads/Rproject")
+source(supportingFunctions.R)
+source("supportingFunctions.R")
+timeDistribution <- function(file1, file2){
+data1 <- read.csv(file1)
+data2<- read.csv(file1)
+infected1 <- data1(all1, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0| age <122)
+infected2 <- data2(all1, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0| age <122)
+ggplot() + geom_histogram(data=infected, aes(x=dayofYear,color="red"), binwidth = 1) +theme_classic()
+ggplot() + geom_histogram(data=infected, aes(x=dayofYear,color="blue"), binwidth = 1) +theme_classic()
+}
+summarizeData("countryY")
+#Set Working Directory
+setwd("/Users/elias/Downloads/Rproject")
+#Initialize ggplot2
+library(ggplot2)
+source("supportingFunctions.R")
+summarizeData("countryY")
+convertDelimiter("countryY")
+compileCSV("countryY")
+compileCSV("countryX")
+compileCSV("countryY")
+compileCSV("countryY")
+compileCSV("countryY")
+compileCSV("countryX")
+timeDistribution("countryY/allData.csv","countryX/allData.csv")
+source("supportingFunctions.R")
+timeDistribution("countryY/allData.csv","countryX/allData.csv")
+timeDistribution("countryY/allData.csv","countryX/allData.csv")
+timeDistribution <- function(file1, file2){
+data1 <- read.csv(file1)
+data2<- read.csv(file2)
+infected1 <- data1(all1, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0| age <122)
+infected2 <- data2(all2, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0| age <122)
+ggplot() + geom_histogram(data=infected1, aes(x=dayofYear,color="red"), binwidth = 1) +theme_classic()
+ggplot() + geom_histogram(data=infected2, aes(x=dayofYear,color="blue"), binwidth = 1) +theme_classic()
+}
+timeDistribution("countryY/allData.csv","countryX/allData.csv")
+timeDistribution("countryY/allData.csv","countryX/allData.csv")
+timeDistribution <- function(file1, file2){
+data1 <- read.csv(file1)
+data2 <- read.csv(file2)
+infected1 <- subset(data1, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0| age <122)
+infected2 <- subset(data2, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0| age <122)
+ggplot() + geom_histogram(data=infected1, aes(x=dayofYear,color="red"), binwidth = 1) +theme_classic()
+ggplot() + geom_histogram(data=infected2, aes(x=dayofYear,color="blue"), binwidth = 1) +theme_classic()
+}
+timeDistribution("countryY/allData.csv","countryX/allData.csv")
+markerDistribution <- function(file1, file2){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+}
+timeDistribution("countryY/allData.csv","countryX/allData.csv")
+timeDistribution("countryY/allData.csv","countrY/allData.csv")
+timeDistribution("countryY/allData.csv","countryY/allData.csv")
+timeDistribution("countryX/allData.csv","countryX/allData.csv")
+timeDistribution("countryX/allData.csv","countryX/allData.csv")
+timeDistribution("countryX/allData.csv","countryX/allData.csv")
+timeDistribution("countryY/allData.csv","countryY/allData.csv")
+firstInfection <- function(file){
+data <- read.csv(file)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+}
+dir("countryY")
+firstInfection("countryY/screen_120.csv")
+firstInfection("countryY/allData.csv")
+firstInfection <- function(file){
+data <- read.csv(file)
+infected <- subset(data, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+numinfected <- nrow(infected)
+print(numinfected)
+}
+firstInfection("countryY/allData.csv")
+firstInfection("countryY/screen_120.csv")
+firstInfection <- function(file){
+data <- read.csv(file)
+infected <- subset(data, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+firstinfection <- min(infected$dayofYear)
+print(firstinfection)
+}
+firstInfection("countryY/screen_120.csv")
+firstInfection("countryY/allData.csv")
+firstInfection("countryX/allData.csv")
+markerDistribution <- function(file1){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(marker01, marker02, marker03, marker04, marker05, marker06, marker07, marker08, marker09, marker10)
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+markerDistribution <- function(file1){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(marker01, marker02, marker03, marker04, marker05, marker06, marker07, marker08, marker09, marker10),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+}
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(marker01, marker02, marker03, marker04, marker05, marker06, marker07, marker08, marker09, marker10),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+ggplot(data = df, aes(x=marker, y= count))+geom_bar()
+}
+markerDistribution("countryX/allData.csv")
+markerDistribution("countryX/allData.csv")
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+ggplot(data = df, aes(x=marker, y= count))+geom_bar()
+}
+markerDistribution("countryX/allData.csv")
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+print(df)
+ggplot(data = df, aes(x=marker, y= count))+geom_bar()
+}
+markerDistribution("countryX/allData.csv")
+ggplot()+geom_bar(data = df, aes(x=marker, y= count))
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+print(df)
+ggplot()+geom_bar(data = df, aes(x=marker, y= count))
+}
+markerDistribution("countryX/allData.csv")
+ggplot()+geom_bar(data = df, aes(x=marker, y= count, color =red))+theme_classic()
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+print(df)
+ggplot()+geom_bar(data = df, aes(x=marker, y= count, color =red))+theme_classic()
+}
+markerDistribution("countryX/allData.csv")
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+print(df)
+ggplot(df, aes(x=marker))+geom_bar(aes(y= count, color =red))+theme_classic()
+}
+markerDistribution("countryX/allData.csv")
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+print(df)
+ggplot(data = df, aes(x=marker, y = count)) + geom_bar(stat=summary)+theme_classic()
+}
+markerDistribution("countryX/allData.csv")
+ggplot(data = df, aes(x=marker, y = count)) + geom_bar(stat="summary")+theme_classic()
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+print(df)
+ggplot(data = df, aes(x=marker, y = count)) + geom_bar(stat="summary")+theme_classic()
+}
+markerDistribution("countryX/allData.csv")
+#This function summarizes the data of a file
+#Provides total number of screens as well as the percent of patients infected
+#As well as the number of patients infected by sex and percent of patients infected by sex
+#In addition a graph of the patient age distribution
+summarizeData<- function(file){
+data <- read.csv(file)
+#Removes unrealistic data of patients older than 122, as some patients were reported to be over 400 years old
+all <- subset(data, age<122)
+#Total number of rows is equal to the number of screens
+numscreen <- nrow(all)
+#Subsets the data for patients with a single marker present in any of the markers
+infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+#Total number of rows is equal to the number of infected
+numinfected <- nrow(infected)
+#Number screened by gender
+nummalescreen <-nrow(subset(all, gender == "male"))
+numfemalescreen <-nrow(subset(all, gender == "female"))
+#Number of  infected by gender
+nummaleinfected <- nrow(subset(infected, gender == "male"))
+numfemaleinfected <- nrow(subset(infected, gender == "female"))
+#Percent infected
+percentinfected = numinfected/numscreen
+malepercentinfected = nummaleinfected/nummalescreen
+femalepercentinfected = numfemaleinfected/numfemalescreen
+#Print functions
+print(paste("Percent of patients screened", numscreen, "with an infection rate of", percentinfected))
+print(paste("Percent of male patients screened", numscreen, "with an infection rate of", malepercentinfected))
+print(paste("Percent of female patients screened", numscreen, "with an infection rate of", femalepercentinfected))
+#Histogram of infected patients by age
+ggplot() + geom_histogram(data=infected, aes(x=age,color="red"), binwidth = 1) +theme_classic()
+}
+#Determines the date of first infection for a given country from summary data
+firstInfection <- function(file){
+data <- read.csv(file)
+#Subsets the data for patients with a single marker present in any of the markers
+infected <- subset(data, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)
+print(min(infected$dayofYear))
+}
+#In which country (X or Y) did the disease outbreak likely begin?
+firstInfection("countryY/allData.csv")
+firstInfection("countryX/allData.csv")
+markerDistribution("countryY/allData.csv")
+markerDistribution("countryX/allData.csv")
+markerDistribution("countryX/allData.csv")
+markerDistribution("countryX/allData.csv")
+markerDistribution("countryY/allData.csv")
+("countryX/allData.csv")
+markerDistribution("countryX/allData.csv")
+markerDistribution("countryY/allData.csv")
+summarizeData(allData.csv)
+summarizeData("allData.csv")
+summarizeData("allData.csv")
+source("supportingFunctions.R")
+summarizeData("allData.csv")
+#Compiles all .csv files in a single directory
+#The user has 3 options in NA choice, remove rows with NAs through removeNA, include NAs but be warned of their presence through warnNA, or include NAs without warning through ignoreNA
+compileCSV<- function(directory, choice){
+#Deletes the output file in the event that it already exists
+file.remove(paste(directory, "allData.csv", sep = "/"))
+#Used to define the first addition to a file which will be later changed to FALSE
+first = TRUE
+#Object with all .csv files in the directory
+filedir <- dir(path = directory, pattern = ".csv")
+if(choice == "warnNA"){ print("Warning this summary data may contain NAs")}
+#Loops through all .csv files in the directory
+for(i in filedir){
+#Stores the data in .csv files as temporary value
+data2 <- read.csv(paste(directory,i, sep = "/"))
+#Remove NAs if choice is removeNA
+if(choice=="removeNA"){ data <- na.omit(data2)}
+#Coverts directory name(ex. countryX) to indenity (ex. X)
+country <- gsub("country","", directory)
+#Replicates country identity for the number of rows in the directory
+country <- rep(country, nrow(data2))
+#Adds a column with country identity to data
+data2 <- cbind(data2, country)
+#Removes all non-numerical characters from file name
+dayofYear <- gsub("[^0-9]", "", i)
+#Replicates date for the number of rows in the directory
+dayofYear <- rep(dayofYear, nrow(data2))
+#Adds a column with date to data
+data2 <- cbind(data2, dayofYear)
+#If this isn't the first entry then column names will be excluded
+if(first==FALSE){
+write.table(data2, file = paste(directory,"allData.csv", sep ="/"), append =T, row.names = F, col.names = F, sep = ",")
+}
+#If this is the first entry then column names will be included
+else{
+first = FALSE
+write.table(data2, file = paste(directory,"allData.csv", sep ="/"), append = F, row.names=F, col.names = T, sep = ",")
+}
+}
+}
+source("supportingFunctions.R")
+#Compiles the CSV data for each country into a file allData.csv for future analysis
+compileCSV("countryY", "ignoreNA")
+#Compiles the CSV data for each country into a file allData.csv for future analysis
+compileCSV("countryY", "warnNA")
+compileCSV("countryX", "ignoreNA")
+compileCSV("countryX", "warnNA")
+#Compiles the CSV data for each country into a file allData.csv for future analysis
+compileCSV("countryY", "removeNA")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+#Provides the number of markers present by marker for a given country from summary data
+markerDistribution <- function(file){
+data <- read.csv(file)
+all <- subset(data, age<122)
+#Creates a dataframe with the markers 1,10 and corresponding total marker count
+df <- data.frame(marker = c(seq.int(1,10,by =1)),
+count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+#bar chart of marker distribution
+ggplot(data = df, aes(x=marker, y = count)) + geom_bar(fill = "blue")+theme_classic()
+}
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+#Country X has extremely high levels of markers 1-5
+markerDistribution("countryX/allData.csv")
+#Country X has extremely high levels of markers 1-5
+markerDistribution("countryX/allData.csv")
+source("supportingFunctions.R")
+#Country X has extremely high levels of markers 1-5
+markerDistribution("countryX/allData.csv")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+source("supportingFunctions.R")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+source("supportingFunctions.R")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+compileCSV("countryX", "removeNA")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+#Country X has extremely high levels of markers 1-5
+markerDistribution("countryX/allData.csv")
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
diff --git a/analysis.R b/analysis.R
new file mode 100644
index 0000000..2f6caa2
--- /dev/null
+++ b/analysis.R
@@ -0,0 +1,39 @@
+
+#Set Working Directory
+setwd("/Users/elias/Downloads/Rproject")
+#Initialize ggplot2
+library(ggplot2)
+
+#Accesses supporting functions
+source("supportingFunctions.R")
+
+#covnerts all .txt files into comma delimited .csv files for countryY
+convertDelimiter("countryY")
+
+
+#Compiles the CSV data for each country into a file allData.csv for future analysis with NAs removed
+compileCSV("countryY", "removeNA")
+compileCSV("countryX", "removeNA")
+
+#In which country (X or Y) did the disease outbreak likely begin?
+#The first infection for country Y is 139
+firstInfection("countryY/allData.csv")
+#The first infection for country X is 120
+firstInfection("countryX/allData.csv")
+#As Country X had infections at day 120, 19 days prior to country Y, the infection likely began in country X
+
+#If Country Y develops a vaccine for the disease, it it likely to work for Country X?
+#Country Y has high levels of markers 6 & 7, with slightly lower levels of markers 7-10
+#and moderate levels of markers 4&5 with nearly no levels of markers 1-3
+markerDistribution("countryY/allData.csv")
+#Country X has extremely high levels of markers 1-5
+markerDistribution("countryX/allData.csv")
+
+#As country Y is developed the vaccine they would likely develop it for markers 5-10
+#These markers are present at low levels in country X
+#As such the country Y vaccine would likely not work for country X
+
+#Summarizes data for both countries form the file allData.csv
+summarizeData("allData.csv")
+
+#The disease appears to infect both sexes fairly equally and appears to mostly infect younger patients under 20 years old
diff --git a/countryX/allData.csv b/countryX/allData.csv
new file mode 100644
index 0000000..5d360ad
--- /dev/null
+++ b/countryX/allData.csv
@@ -0,0 +1,20063 @@
+"gender","age","marker01","marker02","marker03","marker04","marker05","marker06","marker07","marker08","marker09","marker10","country","dayofYear"
+"female",8,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",7,0,0,1,0,0,0,0,0,0,0,"X","120"
+"female",6,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",15,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",12,0,0,1,0,0,0,0,0,0,0,"X","120"
+"female",7,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",16,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",6,0,0,0,1,0,0,0,0,0,0,"X","120"
+"female",4,0,0,1,0,0,0,0,0,0,0,"X","120"
+"female",4,0,0,1,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",41,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",143,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",4,1,0,0,0,0,0,0,0,0,0,"X","120"
+"male",37,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",19,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",8,0,0,0,1,0,0,0,0,0,0,"X","120"
+"male",8,1,0,0,0,0,0,0,0,0,0,"X","120"
+"male",6,0,0,0,0,1,0,0,0,0,0,"X","120"
+"male",22,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",10,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",8,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",17,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",29,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",15,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",32,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",28,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",27,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",34,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",28,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",14,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",6,0,1,0,0,0,0,0,0,0,0,"X","120"
+"male",24,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",16,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",3,0,0,0,1,0,0,0,0,0,0,"X","120"
+"male",25,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",8,0,0,0,0,1,0,0,0,0,0,"X","120"
+"female",10,0,1,0,0,0,0,0,0,0,0,"X","120"
+"female",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",17,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",30,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",22,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",9,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",33,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",2,0,1,0,0,0,0,0,0,0,0,"X","120"
+"female",6,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",3,1,0,1,0,0,0,0,0,0,0,"X","120"
+"male",4,1,0,0,0,0,0,0,0,0,0,"X","120"
+"male",12,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",3,1,0,1,0,0,0,0,0,0,0,"X","120"
+"female",3,1,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",36,1,1,0,0,1,0,0,0,0,0,"X","120"
+"female",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",7,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",10,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",110,0,0,0,1,0,0,0,0,0,0,"X","120"
+"male",15,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",38,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",8,1,0,0,0,0,0,0,0,0,0,"X","120"
+"male",14,0,0,0,1,0,0,0,0,0,0,"X","120"
+"male",25,0,1,0,0,0,0,0,0,0,0,"X","120"
+"female",20,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",15,0,0,0,0,1,0,0,0,0,0,"X","120"
+"female",15,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",7,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",21,0,0,0,1,0,0,0,0,0,0,"X","120"
+"female",19,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",22,0,1,0,0,0,0,0,0,0,0,"X","120"
+"female",9,0,0,0,0,1,0,0,0,0,0,"X","120"
+"female",3,0,0,0,0,1,0,0,0,0,0,"X","120"
+"male",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",113,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",12,1,0,0,0,0,0,0,0,0,0,"X","120"
+"male",9,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",13,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",15,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",8,0,0,0,0,1,0,0,0,0,0,"X","120"
+"male",17,0,1,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",22,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",44,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",17,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",6,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",3,0,1,0,0,0,0,0,0,0,0,"X","120"
+"female",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,1,0,0,0,0,"X","120"
+"male",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",4,0,0,1,0,0,0,0,0,0,0,"X","120"
+"female",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",9,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",7,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",5,0,0,0,0,1,0,0,0,0,0,"X","120"
+"female",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",9,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",31,0,0,0,1,0,0,0,0,0,0,"X","120"
+"male",24,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",16,1,0,0,0,0,0,0,0,0,0,"X","120"
+"female",24,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",14,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",6,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",13,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",11,1,1,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,1,0,0,0,0,0,"X","120"
+"male",20,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",15,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",22,0,0,1,0,0,0,0,0,0,0,"X","120"
+"male",3,1,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",9,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",8,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",7,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",15,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",17,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",10,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",9,0,0,0,0,1,0,0,0,0,0,"X","120"
+"female",16,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",17,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",13,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",21,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",25,1,0,0,0,0,0,0,0,0,0,"X","120"
+"female",2,0,0,1,0,0,0,0,0,0,0,"X","120"
+"male",7,0,0,0,1,0,0,0,0,0,0,"X","120"
+"female",10,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",1,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",11,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",4,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",7,1,0,0,0,0,0,0,0,0,0,"X","120"
+"female",8,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",9,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,1,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",22,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",21,0,0,1,0,0,0,0,0,0,0,"X","120"
+"female",5,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",10,0,1,0,0,0,0,0,0,0,0,"X","120"
+"female",1,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",1,0,0,1,0,0,0,0,0,0,0,"X","120"
+"male",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",6,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",9,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",10,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",7,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",2,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",5,0,0,0,0,1,0,0,0,0,0,"X","120"
+"female",16,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",3,0,0,0,0,0,0,0,0,0,0,"X","120"
+"female",21,0,0,0,0,0,0,0,0,0,0,"X","120"
+"male",33,0,0,0,0,1,0,0,0,0,0,"X","120"
+"female",18,0,0,0,0,1,0,0,0,0,0,"X","120"
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diff --git a/countryY/allData.csv b/countryY/allData.csv
new file mode 100644
index 0000000..84a904b
--- /dev/null
+++ b/countryY/allData.csv
@@ -0,0 +1,19827 @@
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diff --git a/countryY/screen_120.csv b/countryY/screen_120.csv
index 1d6083f..beb25ad 100644
--- a/countryY/screen_120.csv
+++ b/countryY/screen_120.csv
@@ -1,498 +1,498 @@
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index bb35cef..0000000
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diff --git a/countryY/screen_121.csv b/countryY/screen_121.csv
index 7b3f944..8626432 100644
--- a/countryY/screen_121.csv
+++ b/countryY/screen_121.csv
@@ -1,485 +1,485 @@
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deleted file mode 100644
index 6e158f9..0000000
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diff --git a/countryY/screen_122.csv b/countryY/screen_122.csv
index a415351..d2a825a 100644
--- a/countryY/screen_122.csv
+++ b/countryY/screen_122.csv
@@ -1,480 +1,480 @@
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deleted file mode 100644
index 1f99373..0000000
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diff --git a/countryY/screen_123.csv b/countryY/screen_123.csv
index 1aa0849..54879de 100644
--- a/countryY/screen_123.csv
+++ b/countryY/screen_123.csv
@@ -1,253 +1,253 @@
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diff --git a/countryY/screen_123.txt b/countryY/screen_123.txt
deleted file mode 100644
index 19eee64..0000000
--- a/countryY/screen_123.txt
+++ /dev/null
@@ -1,253 +0,0 @@
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diff --git a/countryY/screen_124.csv b/countryY/screen_124.csv
index 8ada20c..4ed0168 100644
--- a/countryY/screen_124.csv
+++ b/countryY/screen_124.csv
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diff --git a/countryY/screen_124.txt b/countryY/screen_124.txt
deleted file mode 100644
index 56ea64b..0000000
--- a/countryY/screen_124.txt
+++ /dev/null
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diff --git a/countryY/screen_125.csv b/countryY/screen_125.csv
index f57e772..7c8d4ff 100644
--- a/countryY/screen_125.csv
+++ b/countryY/screen_125.csv
@@ -1,251 +1,251 @@
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index 86f0f76..0000000
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diff --git a/countryY/screen_126.csv b/countryY/screen_126.csv
index fb7c0dd..aa41fd3 100644
--- a/countryY/screen_126.csv
+++ b/countryY/screen_126.csv
@@ -1,288 +1,288 @@
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diff --git a/countryY/screen_126.txt b/countryY/screen_126.txt
deleted file mode 100644
index 670b317..0000000
--- a/countryY/screen_126.txt
+++ /dev/null
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diff --git a/countryY/screen_127.csv b/countryY/screen_127.csv
index 77ce93f..6ac61af 100644
--- a/countryY/screen_127.csv
+++ b/countryY/screen_127.csv
@@ -1,250 +1,250 @@
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index 3616248..93bf356 100644
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diff --git a/countryY/screen_128.txt b/countryY/screen_128.txt
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index 1f3a4e1..0000000
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index bac88c7..837d546 100644
--- a/countryY/screen_129.csv
+++ b/countryY/screen_129.csv
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diff --git a/countryY/screen_129.txt b/countryY/screen_129.txt
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index 96707b1..0000000
--- a/countryY/screen_129.txt
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diff --git a/countryY/screen_130.csv b/countryY/screen_130.csv
index b40e16e..7c9434e 100644
--- a/countryY/screen_130.csv
+++ b/countryY/screen_130.csv
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diff --git a/countryY/screen_130.txt b/countryY/screen_130.txt
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diff --git a/countryY/screen_131.csv b/countryY/screen_131.csv
index 1a5f3be..242d101 100644
--- a/countryY/screen_131.csv
+++ b/countryY/screen_131.csv
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diff --git a/countryY/screen_131.txt b/countryY/screen_131.txt
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index 7c20a14..0000000
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index bb3557f..1d8eebb 100644
--- a/countryY/screen_132.csv
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index 7fe3415..0000000
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index b23d6a1..66bffbb 100644
--- a/countryY/screen_133.csv
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diff --git a/countryY/screen_134.csv b/countryY/screen_134.csv
index 1160ab4..7c045e0 100644
--- a/countryY/screen_134.csv
+++ b/countryY/screen_134.csv
@@ -1,225 +1,225 @@
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diff --git a/countryY/screen_134.txt b/countryY/screen_134.txt
deleted file mode 100644
index f074e60..0000000
--- a/countryY/screen_134.txt
+++ /dev/null
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diff --git a/countryY/screen_135.csv b/countryY/screen_135.csv
index a6caab9..e4cdd44 100644
--- a/countryY/screen_135.csv
+++ b/countryY/screen_135.csv
@@ -1,398 +1,398 @@
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index fbc1e5d..0000000
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diff --git a/countryY/screen_136.csv b/countryY/screen_136.csv
index 113e940..96bc9c3 100644
--- a/countryY/screen_136.csv
+++ b/countryY/screen_136.csv
@@ -1,469 +1,469 @@
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index e4ec690..0000000
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diff --git a/countryY/screen_137.csv b/countryY/screen_137.csv
index 710dbdc..422e358 100644
--- a/countryY/screen_137.csv
+++ b/countryY/screen_137.csv
@@ -1,302 +1,302 @@
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diff --git a/countryY/screen_137.txt b/countryY/screen_137.txt
deleted file mode 100644
index 7717cf9..0000000
--- a/countryY/screen_137.txt
+++ /dev/null
@@ -1,302 +0,0 @@
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diff --git a/countryY/screen_138.csv b/countryY/screen_138.csv
index 6dea3cf..a717d61 100644
--- a/countryY/screen_138.csv
+++ b/countryY/screen_138.csv
@@ -1,463 +1,463 @@
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diff --git a/countryY/screen_138.txt b/countryY/screen_138.txt
deleted file mode 100644
index d4f2ea9..0000000
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diff --git a/countryY/screen_139.csv b/countryY/screen_139.csv
index fcd21df..052e10f 100644
--- a/countryY/screen_139.csv
+++ b/countryY/screen_139.csv
@@ -1,378 +1,378 @@
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index 1a856d8..0000000
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index 9278d7a..215f65c 100644
--- a/countryY/screen_140.csv
+++ b/countryY/screen_140.csv
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index ae48f06..0000000
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diff --git a/countryY/screen_141.csv b/countryY/screen_141.csv
index 9fc8c65..49ff445 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..4f9278f 100644
--- a/countryY/screen_142.csv
+++ b/countryY/screen_142.csv
@@ -1,434 +1,434 @@
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diff --git a/countryY/screen_142.txt b/countryY/screen_142.txt
deleted file mode 100644
index 7fb91a9..0000000
--- a/countryY/screen_142.txt
+++ /dev/null
@@ -1,434 +0,0 @@
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diff --git a/countryY/screen_143.csv b/countryY/screen_143.csv
index 92555e8..2279121 100644
--- a/countryY/screen_143.csv
+++ b/countryY/screen_143.csv
@@ -1,314 +1,314 @@
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diff --git a/countryY/screen_143.txt b/countryY/screen_143.txt
deleted file mode 100644
index 4c798c5..0000000
--- a/countryY/screen_143.txt
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diff --git a/countryY/screen_144.csv b/countryY/screen_144.csv
index af9623a..0c8584f 100644
--- a/countryY/screen_144.csv
+++ b/countryY/screen_144.csv
@@ -1,217 +1,217 @@
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diff --git a/countryY/screen_144.txt b/countryY/screen_144.txt
deleted file mode 100644
index 64f4486..0000000
--- a/countryY/screen_144.txt
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diff --git a/countryY/screen_145.csv b/countryY/screen_145.csv
index 603c2bf..b6005e6 100644
--- a/countryY/screen_145.csv
+++ b/countryY/screen_145.csv
@@ -1,260 +1,260 @@
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diff --git a/countryY/screen_145.txt b/countryY/screen_145.txt
deleted file mode 100644
index e300c60..0000000
--- a/countryY/screen_145.txt
+++ /dev/null
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index 04e80fe..83acf6b 100644
--- a/countryY/screen_146.csv
+++ b/countryY/screen_146.csv
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index 1cdda51..0000000
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diff --git a/countryY/screen_147.csv b/countryY/screen_147.csv
index 502c993..c170d39 100644
--- a/countryY/screen_147.csv
+++ b/countryY/screen_147.csv
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diff --git a/countryY/screen_148.csv b/countryY/screen_148.csv
index 8175ed6..f8cc56d 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..89313a2 100644
--- a/countryY/screen_149.csv
+++ b/countryY/screen_149.csv
@@ -1,251 +1,251 @@
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deleted file mode 100644
index 64e153d..0000000
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diff --git a/countryY/screen_150.csv b/countryY/screen_150.csv
index bd01a9c..9ba6a55 100644
--- a/countryY/screen_150.csv
+++ b/countryY/screen_150.csv
@@ -1,297 +1,297 @@
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diff --git a/countryY/screen_150.txt b/countryY/screen_150.txt
deleted file mode 100644
index 15a6840..0000000
--- a/countryY/screen_150.txt
+++ /dev/null
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diff --git a/countryY/screen_151.csv b/countryY/screen_151.csv
index e2e4b6c..a38670e 100644
--- a/countryY/screen_151.csv
+++ b/countryY/screen_151.csv
@@ -1,330 +1,330 @@
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diff --git a/countryY/screen_151.txt b/countryY/screen_151.txt
deleted file mode 100644
index 43841e0..0000000
--- a/countryY/screen_151.txt
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diff --git a/countryY/screen_152.csv b/countryY/screen_152.csv
index 0b4833a..b4bb06c 100644
--- a/countryY/screen_152.csv
+++ b/countryY/screen_152.csv
@@ -1,389 +1,389 @@
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diff --git a/countryY/screen_152.txt b/countryY/screen_152.txt
deleted file mode 100644
index 35e0a1a..0000000
--- a/countryY/screen_152.txt
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index 136acf1..c62cde0 100644
--- a/countryY/screen_153.csv
+++ b/countryY/screen_153.csv
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diff --git a/countryY/screen_153.txt b/countryY/screen_153.txt
deleted file mode 100644
index 3cd1108..0000000
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diff --git a/countryY/screen_154.csv b/countryY/screen_154.csv
index ca0241d..9300f8c 100644
--- a/countryY/screen_154.csv
+++ b/countryY/screen_154.csv
@@ -1,272 +1,272 @@
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diff --git a/countryY/screen_154.txt b/countryY/screen_154.txt
deleted file mode 100644
index de5c73d..0000000
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diff --git a/countryY/screen_155.csv b/countryY/screen_155.csv
index 83a23fe..cedaf60 100644
--- a/countryY/screen_155.csv
+++ b/countryY/screen_155.csv
@@ -1,420 +1,420 @@
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diff --git a/countryY/screen_155.txt b/countryY/screen_155.txt
deleted file mode 100644
index 52053ec..0000000
--- a/countryY/screen_155.txt
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diff --git a/countryY/screen_156.csv b/countryY/screen_156.csv
index a7bbad2..100372c 100644
--- a/countryY/screen_156.csv
+++ b/countryY/screen_156.csv
@@ -1,369 +1,369 @@
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index 2df7941..0000000
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index ab9c91f..37f26d6 100644
--- a/countryY/screen_157.csv
+++ b/countryY/screen_157.csv
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diff --git a/countryY/screen_158.csv b/countryY/screen_158.csv
index a722190..cde152a 100644
--- a/countryY/screen_158.csv
+++ b/countryY/screen_158.csv
@@ -1,370 +1,370 @@
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diff --git a/countryY/screen_158.txt b/countryY/screen_158.txt
deleted file mode 100644
index 4a33fe1..0000000
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diff --git a/countryY/screen_159.csv b/countryY/screen_159.csv
index a94d5ad..ea740a4 100644
--- a/countryY/screen_159.csv
+++ b/countryY/screen_159.csv
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diff --git a/countryY/screen_159.txt b/countryY/screen_159.txt
deleted file mode 100644
index d745217..0000000
--- a/countryY/screen_159.txt
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diff --git a/countryY/screen_160.csv b/countryY/screen_160.csv
index 42dce4b..d1b2a72 100644
--- a/countryY/screen_160.csv
+++ b/countryY/screen_160.csv
@@ -1,480 +1,480 @@
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index 5e19eff..0000000
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diff --git a/countryY/screen_161.csv b/countryY/screen_161.csv
index 3436247..5fe71e2 100644
--- a/countryY/screen_161.csv
+++ b/countryY/screen_161.csv
@@ -1,309 +1,309 @@
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diff --git a/countryY/screen_161.txt b/countryY/screen_161.txt
deleted file mode 100644
index 02dca2b..0000000
--- a/countryY/screen_161.txt
+++ /dev/null
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diff --git a/countryY/screen_162.csv b/countryY/screen_162.csv
index 64c52db..9d8fee0 100644
--- a/countryY/screen_162.csv
+++ b/countryY/screen_162.csv
@@ -1,435 +1,435 @@
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diff --git a/countryY/screen_162.txt b/countryY/screen_162.txt
deleted file mode 100644
index 7858019..0000000
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diff --git a/countryY/screen_163.csv b/countryY/screen_163.csv
index edfe02d..941cc9b 100644
--- a/countryY/screen_163.csv
+++ b/countryY/screen_163.csv
@@ -1,248 +1,248 @@
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diff --git a/countryY/screen_163.txt b/countryY/screen_163.txt
deleted file mode 100644
index e8783bf..0000000
--- a/countryY/screen_163.txt
+++ /dev/null
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index 8b3e70d..5c282aa 100644
--- a/countryY/screen_164.csv
+++ b/countryY/screen_164.csv
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diff --git a/countryY/screen_164.txt b/countryY/screen_164.txt
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index d9ef97a..0000000
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diff --git a/countryY/screen_165.csv b/countryY/screen_165.csv
index 92112ac..8d05e35 100644
--- a/countryY/screen_165.csv
+++ b/countryY/screen_165.csv
@@ -1,309 +1,309 @@
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diff --git a/countryY/screen_165.txt b/countryY/screen_165.txt
deleted file mode 100644
index bcb7358..0000000
--- a/countryY/screen_165.txt
+++ /dev/null
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diff --git a/countryY/screen_166.csv b/countryY/screen_166.csv
index 10b6ffe..d9018ad 100644
--- a/countryY/screen_166.csv
+++ b/countryY/screen_166.csv
@@ -1,349 +1,349 @@
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diff --git a/countryY/screen_166.txt b/countryY/screen_166.txt
deleted file mode 100644
index 671abf0..0000000
--- a/countryY/screen_166.txt
+++ /dev/null
@@ -1,349 +0,0 @@
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diff --git a/countryY/screen_167.csv b/countryY/screen_167.csv
index 07772dc..f89ac90 100644
--- a/countryY/screen_167.csv
+++ b/countryY/screen_167.csv
@@ -1,489 +1,489 @@
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diff --git a/countryY/screen_167.txt b/countryY/screen_167.txt
deleted file mode 100644
index ed72641..0000000
--- a/countryY/screen_167.txt
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diff --git a/countryY/screen_168.csv b/countryY/screen_168.csv
index 4c33754..cbfcffb 100644
--- a/countryY/screen_168.csv
+++ b/countryY/screen_168.csv
@@ -1,498 +1,498 @@
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diff --git a/countryY/screen_168.txt b/countryY/screen_168.txt
deleted file mode 100644
index b1fedb2..0000000
--- a/countryY/screen_168.txt
+++ /dev/null
@@ -1,498 +0,0 @@
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diff --git a/countryY/screen_169.csv b/countryY/screen_169.csv
index b89d421..e73f49a 100644
--- a/countryY/screen_169.csv
+++ b/countryY/screen_169.csv
@@ -1,241 +1,241 @@
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diff --git a/countryY/screen_169.txt b/countryY/screen_169.txt
deleted file mode 100644
index 5ae8280..0000000
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diff --git a/countryY/screen_170.csv b/countryY/screen_170.csv
index 5b057d0..f6589fa 100644
--- a/countryY/screen_170.csv
+++ b/countryY/screen_170.csv
@@ -1,443 +1,443 @@
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diff --git a/countryY/screen_170.txt b/countryY/screen_170.txt
deleted file mode 100644
index 532ff47..0000000
--- a/countryY/screen_170.txt
+++ /dev/null
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diff --git a/countryY/screen_171.csv b/countryY/screen_171.csv
index 04dbd5d..a01ac18 100644
--- a/countryY/screen_171.csv
+++ b/countryY/screen_171.csv
@@ -1,451 +1,451 @@
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diff --git a/countryY/screen_171.txt b/countryY/screen_171.txt
deleted file mode 100644
index a41292c..0000000
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diff --git a/countryY/screen_172.csv b/countryY/screen_172.csv
index cdb4453..e597bc7 100644
--- a/countryY/screen_172.csv
+++ b/countryY/screen_172.csv
@@ -1,331 +1,331 @@
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diff --git a/countryY/screen_172.txt b/countryY/screen_172.txt
deleted file mode 100644
index 61519a8..0000000
--- a/countryY/screen_172.txt
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diff --git a/countryY/screen_173.csv b/countryY/screen_173.csv
index 704eaa1..3eebcec 100644
--- a/countryY/screen_173.csv
+++ b/countryY/screen_173.csv
@@ -1,298 +1,298 @@
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diff --git a/countryY/screen_173.txt b/countryY/screen_173.txt
deleted file mode 100644
index d24863a..0000000
--- a/countryY/screen_173.txt
+++ /dev/null
@@ -1,298 +0,0 @@
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diff --git a/countryY/screen_174.csv b/countryY/screen_174.csv
index c1cd2ef..1deedc3 100644
--- a/countryY/screen_174.csv
+++ b/countryY/screen_174.csv
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diff --git a/countryY/screen_175.csv b/countryY/screen_175.csv
index 9d00a50..7547fe9 100644
--- a/countryY/screen_175.csv
+++ b/countryY/screen_175.csv
@@ -1,364 +1,364 @@
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diff --git a/file b/file
new file mode 100644
index 0000000..8b9fe31
--- /dev/null
+++ b/file
@@ -0,0 +1,2 @@
+x
+screen_175.txt
diff --git a/supportingFunctions.R b/supportingFunctions.R
new file mode 100644
index 0000000..d800289
--- /dev/null
+++ b/supportingFunctions.R
@@ -0,0 +1,118 @@
+#Elias Issa Rproject
+
+#Set Working Directory
+setwd("/Users/elias/Downloads/Rproject")
+#Initialize ggplot2
+library(ggplot2)
+
+#Converts all .txt files in a directory to csv files
+convertDelimiter<- function(directory){
+    #Object with all .txt file names in given directory
+    filedir <- dir(path = directory, pattern = ".txt")
+    #Loops through all .txt files, reads the content to data and writes a .csv file with the same name, then removes the .txt file
+    for(i in filedir){
+      data <- read.table(paste(directory,i, sep ="/" ), header = T, sep = "")
+      write.csv(data, file = paste(directory, sub(".txt",".csv", i), sep ="/"), quote=F, row.names=F, sep = ",")
+      file.remove(paste(directory,i, sep ="/" ))
+      }
+    }
+#Compiles all .csv files in a single directory
+#The user has 3 options in NA choice, remove rows with NAs through removeNA, include NAs but be warned of their presence through warnNA, or include NAs without warning through ignoreNA 
+compileCSV<- function(directory, choice){
+  #Deletes the output file in the event that it already exists
+  file.remove(paste(directory, "allData.csv", sep = "/"))
+  #Used to define the first addition to a file which will be later changed to FALSE
+  first = TRUE
+  #Object with all .csv files in the directory
+  filedir <- dir(path = directory, pattern = ".csv")
+  if(choice == "warnNA"){ print("Warning this summary data may contain NAs")}
+  #Loops through all .csv files in the directory
+  for(i in filedir){
+    #Stores the data in .csv files as temporary value
+    data2 <- read.csv(paste(directory,i, sep = "/"))
+    #Remove NAs if choice is removeNA
+    if(choice=="removeNA"){ data <- na.omit(data2)}
+  
+    #Coverts directory name(ex. countryX) to indenity (ex. X)
+    country <- gsub("country","", directory)
+    #Replicates country identity for the number of rows in the directory 
+    country <- rep(country, nrow(data2))
+    #Adds a column with country identity to data
+    data2 <- cbind(data2, country)
+    #Removes all non-numerical characters from file name
+    dayofYear <- gsub("[^0-9]", "", i)
+    #Replicates date for the number of rows in the directory
+    dayofYear <- rep(dayofYear, nrow(data2))
+    #Adds a column with date to data
+    data2 <- cbind(data2, dayofYear)
+    #If this isn't the first entry then column names will be excluded
+    if(first==FALSE){
+      write.table(data2, file = paste(directory,"allData.csv", sep ="/"), append =T, row.names = F, col.names = F, sep = ",")
+    }
+    #If this is the first entry then column names will be included
+    else{
+      first = FALSE
+      write.table(data2, file = paste(directory,"allData.csv", sep ="/"), append = F, row.names=F, col.names = T, sep = ",")
+      }
+  }
+}
+
+#This function summarizes the data of a file
+#Provides total number of screens as well as the percent of patients infected
+#As well as the number of patients infected by sex and percent of patients infected by sex
+#In addition a graph of the patient age distribution
+summarizeData<- function(file){
+    data <- read.csv(file)
+    #Removes unrealistic data of patients older than 122, as some patients were reported to be over 400 years old
+    all <- subset(data, age<122)
+    #Total number of rows is equal to the number of screens
+    numscreen <- nrow(all)
+    #Subsets the data for patients with a single marker present in any of the markers
+    infected <- subset(all, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)   
+    #Total number of rows is equal to the number of infected
+    numinfected <- nrow(infected)
+    
+    #Number screened by gender
+    nummalescreen <-nrow(subset(all, gender == "male"))
+    numfemalescreen <-nrow(subset(all, gender == "female"))
+    
+    #Number of  infected by gender
+    nummaleinfected <- nrow(subset(infected, gender == "male"))
+    numfemaleinfected <- nrow(subset(infected, gender == "female"))
+    
+    #Percent infected
+    percentinfected = numinfected/numscreen
+    malepercentinfected = nummaleinfected/nummalescreen
+    femalepercentinfected = numfemaleinfected/numfemalescreen
+
+    #Print functions
+    print(paste("Percent of patients screened", numscreen, "with an infection rate of", percentinfected))
+    print(paste("Percent of male patients screened", nummalescreen, "with an infection rate of", malepercentinfected))
+    print(paste("Percent of female patients screened", numfemalescreen, "with an infection rate of", femalepercentinfected))
+    
+    #Histogram of infected patients by age
+    ggplot() + geom_histogram(data=infected, aes(x=age,color="red"), binwidth = 1) +theme_classic()
+
+}
+
+#Provides the number of markers present by marker for a given country from summary data
+markerDistribution <- function(file){
+  data <- read.csv(file)
+  all <- subset(data, age<122)
+  #Creates a dataframe with the markers 1,10 and corresponding total marker count
+  df <- data.frame(marker = c(seq.int(1,10,by =1)),
+                   count = c(sum(all$marker01),sum(all$marker02),sum(all$marker03),sum(all$marker04),sum(all$marker05),sum(all$marker06),sum(all$marker07),sum(all$marker08),sum(all$marker09),sum(all$marker10)))
+  #bar chart of marker distribution
+   ggplot(data = df, aes(x=marker, y = count)) + geom_bar(stat= "identity")+theme_classic()
+}
+
+#Determines the date of first infection for a given country from summary data
+firstInfection <- function(file){
+  data <- read.csv(file)
+  #Subsets the data for patients with a single marker present in any of the markers
+  infected <- subset(data, marker01 > 0 | marker02 > 0 | marker03 > 0 | marker04 > 0 | marker05 > 0 | marker06 > 0 | marker07 > 0 | marker08 > 0 | marker09 > 0 | marker10 > 0)   
+ #prints the minimum value of day of year to represent the first infection
+   print(min(infected$dayofYear))
+}
+  
+