Function that assists with importing CSV data from Qualtrics into R; it also allows for choosing which categorical variables should be numeric and which labelled.

import_qualtrics_csv

import_csv_qualtrics <- function(file) {
    # import a csv file exported from Qualtrics
    # Qualtrics places variable labels in the second row. 
    # This function removes that second row and returns the data frame.
    # taken from:
    # http://lowlywonk.blogspot.com.au/2011/05/r-code-to-remove-second-line-of.html
    DF <- read.csv(file, skip=2, header=FALSE)
    DF2 <- read.csv(file)
    names(DF) <- names(DF2)
    DF
}
    

import_qualtrics <- function(label_csv_file, numeric_csv_file, numeric_fields = NULL, 
        dputnames = TRUE, export_all = TRUE) {
    # label_csv_file: csv file exported from Qualtrics with labels
    # numeric_csv_file: csv file exported from Qualtrics with numbers instead of labels
    # numeric_fields: variable names for categorical questions where you want to import 
    #                the numeric response
    # dputnames: By default, the function will print all variable names
    #            This is useful. You can then copy and paste the variables
    #            into a vector to include in the "numeric_fields" variable.
    # export_all: By default, the function will export label, numeric, and combined data.frames
    #             If FALSE, then it will just export the combined data.frame.
    ldf <- import_csv_qualtrics(label_csv_file)
    ndf <- import_csv_qualtrics(numeric_csv_file)
    if (dputnames) cat(dput(names(ldf)))
    original_order <- names(ldf)
    cdf <- data.frame(ldf[setdiff(original_order, numeric_fields)], ndf[numeric_fields])
    cdf <- cdf[original_order]
    if (export_all) {
        list(combined = cdf, label = ldf, numeric = ndf)
    } else {
        cdf
    }
}

# Step 1:
# Export CSV data from Qualtrics twice (once with numbers for categories and once with labels)
# and give files clear names

# Step2: Run it once with 
# rcases <- import_qualtrics("raw-data/label-myfile.csv", "raw-data/numeric-myfile.csv")
# identify which variables should be numeric. 
# The dput output makes it easier to select the numeric variables.

# Step 3: Re-run the command including the vector of variable names that are meant to
#     be numeric (e.g., likert survey items, and so on)

# rcases <- import_qualtrics("raw-data/label-myfile.csv", "raw-data/numeric-myfile.csv",
#            numeric_fields = c("item1", "item2"),
#                           dput = FALSE, export_all =  FALSE)