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+#Marlee Shaffer
+##Exercise 9 
+
+#VarCof is a function that reads data from each file in the specified directory 
+#and calculates the coefficient of variation. By default, 50 observations are required
+#to get an output. The column of interest must be numerical and have a header.
+
+#Usage: VarCof(dir = "full directory map", column = "number of column of interest", 
+#x = minimum number of observations (by default, it is 50), override = "Yes" or "No" for 
+#if the number of observations needs to be met)
+
+VarCof<-function(dir, col, x="50", override="No"){
+  #Set the working directory to the directory entered
+  setwd(dir)
+  #List all files in the directory and save them as a variable
+  File<-list.files(dir)
+  #Create an empty vector for variance
+  Variance<-c()
+  #Create an empty vector for error
+  Error<-c()
+  #For each file..
+  for (files in File){
+    #Read the file as a table so the columns can be pulled out 
+    file_i<-read.table(files, header = TRUE, sep=",", stringsAsFactors = FALSE, fill = TRUE)
+    #Pull out column of interest
+    interestcol<-file_i[, col]
+    interestcol.na<-na.omit(interestcol)
+    #Find the number of observations and do math depending on value of x and override
+    if (length(interestcol.na)>=x){ #Greater than or equal to 50, or changed value
+      #Calculate the mean, standard deviation, and variation
+      M<-mean(interestcol.na)
+      SD<-sd(interestcol.na, na.rm = FALSE)
+      Var<-SD/M
+      Variance<-c(Variance, Var)
+      Er<-0
+      Error<-c(Error, Er)
+    }else if (length(interestcol.na)<x && override == "Yes"){
+      #Calculate the mean, standard deviation, and variation, but also give a warning
+      M1<-mean(interestcol.na)
+      SD1<-sd(interestcol.na, na.rm = FALSE)
+      Var1<-M1/SD1
+      Variance<-c(Variance, Var1)
+      Er1<-1
+      Error<-c(Error, Er1)
+    }else{
+      Var2<-0
+      Variance<-c(Variance, Var2)
+      Er2<-2
+      Error<-c(Error, Er2)
+    }
+  }
+  Error0<-print("Error 0: No Error, congrats.")
+  Error1<-print("Error 1:  Warning: There are not enough observations for a reliable calculation, but this error was overlooked by your inputs")
+  Error2<-print("Error 2: Error: There are not enough observations, please add more.")
+  return(data.frame(File, Variance, Error)) 
+  return(Error0,Error1,Error2)
+}
+