updated districtReview and adding script to review all districts at once

Scripts/Scripts_DataReview/DistrictReview.R

-
+### Script to create a table for one district, Aileu, that calculates the sum of times the district's results are above and below the national average
+## If you are running DistrictReview_allDistrict.R then there is no need runnning this script
+#---------------------------------------
 
 
 setwd("~/ownCloud/Timor-Leste/Data/Population/Census_2015/output/NewName/Final")
 filename = "X2.1.a.Table.1.a.Total.population.and.household.type.by.sex.and.Municipality.csv"
-filename = "X2..5.1i.Table.5.1i.Population.by.age.and.sex..Liquiça.csv"
-filename = "X2.2.a.Table.2.a.Total.population.density.and.number.of.households.by.Municipality.csv"
-filename = "X2.21d.Table.21.d.Former.members.of.private.households.living.in.Australia..New.Zealand..or.Other.Pacific.Countries..by.sex..Municipality.and.Administrative.Post.of.household.csv"
+#filename = "X2..5.1i.Table.5.1i.Population.by.age.and.sex..Liquiça.csv"
+#filename = "X2.2.a.Table.2.a.Total.population.density.and.number.of.households.by.Municipality.csv"
+#filename = "X2.21d.Table.21.d.Former.members.of.private.households.living.in.Australia..New.Zealand..or.Other.Pacific.Countries..by.sex..Municipality.and.Administrative.Post.of.household.csv"
 
-TableName = ""
-Above_average = ""
-Below_average = ""
-df = data.frame(TableName,Above_average, Below_average, stringsAsFactors = FALSE)
+df = data.frame(TableName = as.character(),Above_average = as.character(), Below_average = as.character(), stringsAsFactors = FALSE)
 dir.create("Review")
-write.csv(df, "Review/Aileu_Review.csv", row.names = FALSE)
+write.table(df, "Review/Aileu_Review.csv", sep = ",", row.names = FALSE, col.names = TRUE)
 districtReview = function(filename) {
   table = read.csv(filename, header = TRUE, stringsAsFactors = FALSE)
 ## clean up some tables with have whitespace in the first column  

Scripts/Scripts_DataReview/DistrictReview_allDistricts.R

+
+### Script to create 13 datasheets for each of the 13 districts showing above and below national average counts
+#---------------------------
+
+setwd("~/ownCloud/Timor-Leste/Data/Population/Census_2015/output/NewName/Final")
+filename = "X2.1.a.Table.1.a.Total.population.and.household.type.by.sex.and.Municipality.csv"
+#filename = "X2..5.1i.Table.5.1i.Population.by.age.and.sex..Liquiça.csv"
+#filename = "X2.2.a.Table.2.a.Total.population.density.and.number.of.households.by.Municipality.csv"
+#filename = "X2.21d.Table.21.d.Former.members.of.private.households.living.in.Australia..New.Zealand..or.Other.Pacific.Countries..by.sex..Municipality.and.Administrative.Post.of.household.csv"
+#district = "AILEU"
+
+districts <- read.csv(filename, stringsAsFactors = FALSE)
+districts <- as.character(districts[,1])
+dir.create("Review")
+
+districtReview = function(filename, district = NULL) {
+  if(!is.null(district)) {
+    table = read.csv(filename, header = TRUE, stringsAsFactors = FALSE)
+    ## clean up some tables with have whitespace in the first column  
+    table[,1] = trimws(table[,1])
+    ## check to see if Aileu exists in the first column. If it does perform the "if" statement, if not perform "else" 
+    if(district %in% table[,1]) {
+      avg = data.frame(apply(table[2:ncol(table)], 2, mean))
+      #create Aileu tables
+      ## future plan to make this more dynamic so it isn't just searching for Aileu
+      df = table[grepl(district, table[,1], fixed = FALSE, ignore.case = TRUE),]    
+      df = data.frame(t(df[1,]))
+      districtName = df[1,1]
+      df = data.frame(df[2:nrow(df),])
+      #row.names(Aileu) = rownames[2:nrow(Aileu)]
+      #Aileu = data.frame(Aileu)
+      names(df) = districtName
+      ## make sure column values are numeric, sometimes stored as factors
+      
+      df[,1] <- as.numeric(as.character(df[,1]))
+      ## combine Aileu and national averages
+      df = data.frame(cbind(df, avg))
+      #compare district results with national average
+      districtAboveAvg = data.frame(df[,1] > df[,2])
+      df = cbind(df, districtAboveAvg)
+      #create a summary table of true/false results
+      Above_average = sum(df$df...1....df...2.=="TRUE")
+      Below_average = sum(df$df...1....df...2.=="FALSE")
+      dat = data.frame(cbind(Above_average, Below_average))
+      names(dat) = c(paste(districtName,"Above_average", sep = "_"),paste(districtName, "Below_average", sep = "_"))
+      x  = cbind(names(table[1]), dat)
+      ## commented the below out because not sure about combining at this early stage
+      #x  = cbind(names(table[1]), dat)
+      tab = read.table(paste("Review/districtReview",district,"csv", sep = "."), header = TRUE, sep = ",", stringsAsFactors = FALSE)
+      names(x) <- names(tab)
+      ## currently not working. Trying to insert name of the table in the first column of tab
+      tab = rbind(tab,x)
+      write.table(tab, paste("Review/districtReview",district,"csv", sep = "."), sep = ",", row.names = FALSE, col.names = TRUE)
+    } else {
+      df = read.table(paste("Review/districtReview",district,"csv", sep = "."), header = TRUE, sep = ",", stringsAsFactors = FALSE)
+      x = c(names(table[1]),c(NA, NA))
+      write.table(rbind(df, x), paste("Review/districtReview",district,"csv", sep = "."), sep = ",", row.names = FALSE, col.names = TRUE)
+    }
+  }
+}
+
+
+#districtReview(filename, district = "AILEU")
+
+districtReview_all=function(pattern, district){
+  #district = district
+  filenames = list.files(path = ".", pattern = pattern)
+    for (f in filenames) {
+      districtReview(f, district = x)
+    }
+}
+
+#districtReview_all("*.csv")
+
+for (x in districts) {
+  df = data.frame(TableName = character(),Above_average= character(), Below_average = character(), stringsAsFactors = FALSE)
+  write.table(df, file = paste("Review/districtReview",x,"csv", sep = "."), sep = ",", row.names = FALSE, col.names = TRUE)
+  districtReview_all("*.csv", x)
+  #apply names to the columns in the tables
+  df = read.table(paste("Review/districtReview",x,"csv", sep = "."), sep = ",", header = FALSE)
+  names(df) = c("TableName", "Above_average", "Below_average")
+  write.table(df, file = paste("Review/districtReview",x,"csv", sep = "."), sep = ",", row.names = FALSE, col.names = TRUE)
+}
+
+
+
+