Exercise 9 submission with .csv files used for testing code

Exercise09.R

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+## Exercise 9 ##
+## Pulling al of the R programming pieces together ##
+
+#Create function to calculate coeffecient variance of separate files
+covar = function(dir, colNo){
+  covs = 0
+  path = list.files(dir) ##list all the files in the directory
+
+  # read through each file in directory
+  for (i in 1:length(path)){
+    file = paste0(dir,path[i]) ## create a full path name to read in the file in the next line
+    info = read.table(file, header = T, sep=",", stringsAsFactors = F) ## read in tabular data
+
+    #see if file has less than 50 rows/observations and warn user if so
+    if (length(info[,colNo]) < 50){
+      print(paste0("Warning: file ", file[i]," has less 50 oberservations")) 
+
+      #take in the column specified by the user and calculate coefficient of variation
+      covs [i]= (sd(info[,colNo])/mean(info[,colNo]))*100
+
+    } else {
+
+      #take in the column specified by the user and calculate coefficient of variation
+      covs [i]= (sd(info[,colNo])/mean(info[,colNo]))*100
+    }
+  }
+  return(covs) #return the coeffecient of variance values from each file
+}
+
+print("Enter the directory in which you would like to read files from. Be sure to include a '/' at the end of the directory name.")
+userDir = readline(prompt = "Directory: ")
+fileCol = as.integer(readline(prompt = "Which column do you want to find the coeffecient of variance for? "))
+covar(userDir, fileCol) # call function

lessthan50.csv

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+gender,yearsExperience,yearsSchool,wage,,STD,AVG,COV
+female,39,42,6.315295646,EXP,16.94704809,21.56097561,78.60056242
+female,29,16,5.479769979,SCHOOL,15.62857764,25.43902439,61.43544422
+female,43,37,3.642169917,,,,
+female,22,17,4.5933366,,,,
+female,21,42,2.418157461,,,,
+female,31,16,2.09405811,,,,
+female,10,1,5.51200392,,,,
+female,6,45,3.54842716,,,,
+female,5,7,5.81822636,,,,
+female,47,10,3.8277805,,,,
+female,48,13,6.73689368,,,,
+female,30,20,12.86134248,,,,
+female,5,0,7.655561,,,,
+female,20,2,2.44977952,,,,
+female,3,36,6.105662147,,,,
+female,2,40,8.26800588,,,,
+female,33,44,1.862405483,,,,
+female,2,47,3.98089172,,,,
+female,1,30,4.763460178,,,,
+female,7,8,6.380595586,,,,
+female,48,2,5.631123847,,,,
+female,44,10,2.488057325,,,,
+female,16,22,1.223738277,,,,
+female,16,18,1.345653539,,,,
+female,1,33,0.751111645,,,,
+female,47,39,11.33023028,,,,
+female,3,22,3.894757656,,,,
+female,13,23,2.998515251,,,,
+female,18,29,3.267896188,,,,
+female,11,7,1.355197181,,,,
+female,42,6,4.28711416,,,,
+female,10,37,7.624938756,,,,
+female,3,44,4.443786106,,,,
+female,13,28,1.134281476,,,,
+female,42,44,9.064184223,,,,
+female,19,43,3.98089172,,,,
+female,2,42,3.450705238,,,,
+female,33,38,8.096728922,,,,
+female,49,37,8.735213831,,,,
+female,5,44,7.275845174,,,,
+female,45,2,5.51200392,,,,