Question

I’m trying to analyse a large survey created with surveymonkey which has hundreds of columns in the CSV file and the output format is difficult to use as the headers run over two lines.

• Has anybody found a simple way of managing the headers in the CSV file so that the analysis is manageable ?
• How do other people analyse results from Surveymonkey?

Thanks!

Answer 1

What I did in the end was print out the headers using libreoffice labeled as V1,V2, etc. then I just read in the file as

 m1 <- read.csv('Sheet1.csv', header=FALSE, skip=1)

and then just did the analysis against m1$V10, m1$V23 etc…

To get around the mess of multiple columns I used the following little function

# function to merge columns into one with a space separator and then
# remove multiple spaces
mcols <- function(df, cols) {
    # e.g. mcols(df, c(14:18))
        exp <- paste('df[,', cols, ']', sep='', collapse=',' )
        # this creates something like...
        # "df[,14],df[,15],df[,16],df[,17],df[,18]"
        # now we just want to do a paste of this expression...
        nexp <- paste(" paste(", exp, ", sep=' ')")
        # so now nexp looks something like...
        # " paste( df[,14],df[,15],df[,16],df[,17],df[,18] , sep='')"
        # now we just need to parse this text... and eval() it...
        newcol <- eval(parse(text=nexp))
        newcol <- gsub('  *', ' ', newcol) # replace duplicate spaces by a single one
        newcol <- gsub('^ *', '', newcol) # remove leading spaces
        gsub(' *$', '', newcol) # remove trailing spaces
}
# mcols(df, c(14:18))

No doubt somebody will be able to clean this up!

To tidy up Likert-like scales I used:

# function to tidy c('Strongly Agree', 'Agree', 'Disagree', 'Strongly Disagree')
tidylik4 <- function(x) {
  xlevels <- c('Strongly Disagree', 'Disagree', 'Agree', 'Strongly Agree')
  y <- ifelse(x == '', NA, x)
  ordered(y, levels=xlevels)
}

for (i in 44:52) {
  m2[,i] <- tidylik4(m2[,i])
}

Feel free to comment as no doubt this will come up again!