gistfile1.r

#Reproducible example

lik <- structure(list(Relevant = structure(c(6L, 5L, 6L, 2L, 5L, 4L, 5L, 5L, 6L, 2L, 6L, 3L, 5L, 4L, 5L, 3L, 2L, 2L, 4L, NA, 2L, 6L, NA, 5L, 5L, 5L, 5L, 5L, 6L, 6L), .Label = c("0", "Agree", "Disagree", "Neutral", "Strongly Agree", "Strongly Disagree"), class = "factor"), Help.career = structure(c(3L, 5L, 6L, 2L, 5L, 2L, 5L, 5L, 6L, 2L, 6L, 3L, 5L, 4L, 3L, 2L, 2L, 2L, 2L, NA, 6L, 6L, 2L, 5L, 5L, 5L, 5L, 4L, 6L, 6L), .Label = c("0", "Agree", "Disagree", "Neutral", "Strongly Agree", "Strongly Disagree"), class = "factor"), Earn.credential = structure(c(6L, 5L, 2L, 2L, 2L, 4L, 5L, 5L, 6L, 4L, 6L, 2L, 5L, 2L, 3L, 3L, 2L, 4L, 5L, NA, 3L, 6L, NA, 6L, 3L, 4L, 4L, 6L, 6L, 2L), .Label = c("0", "Agree", "Disagree", "Neutral", "Strongly Agree", "Strongly Disagree"), class = "factor"), Prestigious.U = structure(c(6L, 5L, 2L, 2L, 2L, 4L, 5L, 2L, 6L, 3L, 6L, 4L, 5L, 4L, 3L, 3L, 2L, 4L, 2L, NA, 6L, 5L, NA, 2L, 3L, 5L, 2L, 5L, 6L, 6L), .Label = c("0", "Agree", "Disagree", "Neutral", "Strongly Agree", "Strongly Disagree"), class = "factor"), Fun = structure(c(5L, 5L, 2L, 5L, 5L, 5L, 5L, 2L, 5L, 5L, 5L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 5L, 5L, 2L, 5L, 5L, 5L, 2L, 2L, 6L, 5L), .Label = c("0", "Agree", "Disagree", "Neutral", "Strongly Agree", "Strongly Disagree"), class = "factor"), usercat = structure(c(7L, 5L, 4L, 3L, 5L, 3L, 5L, 7L, 3L, 3L, 5L, 7L, 7L, 3L, 5L, 5L, 3L, 3L, 3L, 2L, 3L, 5L, 3L, 5L, 3L, 7L, 3L, 3L, 4L, 3L), .Label = c("", "Academic / Professor", "Lifelong Learner", "None of the above", "Professional", "Researcher", "Student (University/College)"), class = "factor")), .Names = c("Relevant", "Help.career", "Earn.credential", "Prestigious.U", "Fun", "usercat"), row.names = c(NA, 30L), class = "data.frame")

reshape.likert <- function(x, factors=c("Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree"), columns="ALL") {
  row.names(x) <- NULL
  if (columns=="ALL") { cols <- x} else { cols <- x[,columns] } # choose relevant columns
  cols <- sapply(cols, function(y) table(factor(y))) # get summary counts for each line
  cols <- t(cols) # flip the axis
  #cols <- cols[,factors] # resort the factors - this gives an error if not data.frame
  return(cols)
}

#Why do these two give totally different answers (different data structures)?
reshape.likert(lik[,c(1:4)])
reshape.likert(lik[,c(1:5)])