Lan Li_Exercise 9

answer codes 11-18.R

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+# function cvar that can return the coefficient_variation of selected column in every *.cvs files in a selected directory.
+#   dir -- directory. 
+#   select_col -- selected column name
+#   z -- reliable observation
+
+
+rm(list = ls())
+setwd("/Users/lillian/Desktop/Biocomp_tutorial11/")
+
+cvar=function(dir = "test", select_col = c("wage"), z = 50){
+  data_files = list.files(dir,
+                          full.names = TRUE)
+  results <- data.frame(file_name = vector(mode = "character", length = length(data_files)),
+                        coefficient_variation = vector(mode = "numeric", length = length(data_files)),
+                        file_message = vector(mode = "character", length = length(data_files)))
+  for (i in 1:length(data_files)){
+    filename <- data_files[i]
+    data <- read.csv(filename)
+    y <- tryCatch(length(data[ , select_col]), error= function(e) {return(0)}  )
+    if (y == 0) {
+      cv = c("")
+      mes = c("column not exist")
+      results$file_name[i] <- filename
+      results$coefficient_variation[i] <- cv
+      results$file_message[i] <- mes
+      next}
+
+    datacol=data[ , select_col]
+    len_selectcol = length(datacol)  
+    if(len_selectcol >= z){
+      cv = sd(datacol, na.rm=T) / mean(datacol, na.rm=T)
+      mes = c("meet criteria")
+      results$file_name[i] <- filename
+      results$coefficient_variation[i] <- cv
+      results$file_message[i] <- mes
+    }else if(len_selectcol < z){
+      cv = sd(datacol, na.rm=T) / mean(datacol, na.rm=T)
+      mes = c("warning: less than reliable observations")
+      results$file_name[i] <- filename
+      results$coefficient_variation[i] <- cv
+      results$file_message[i] <- mes
+    }
+  }
+  print(results)
+}