How to dynamically change data type of columns in data frame

The platform from which I'm importing data to R does not support specifying the data type, hence all my columns are character. I have an Excel file that specifies which columns are factor, including the relevant labels and levels. Now, I'm trying to write a function to dynamically change the data type of various columns of my data.frame

Thanks to the excellent answer to this question (dplyr - mutate: use dynamic variable names), I managed to write the following function, in which I dynamically set the column name to the mutate function.

readFactorData <- function(filepath) {
    t <- read.xlsx(filepath)
    sapply(nrow(t), function(i) {
      colname <- as.character(t[i, "Item"])
      factorLevels <- t[i, 3:ncol(t)][which(!is.na(t[i, 3:ncol(t)]))]
      totalLevels <- length(factorLevels)
      listOfLabels <- as.character(unlist(factorLevels))

      mutate(d, !!colname := factor(d[[colname]], labels=(1:totalLevels), levels=listOfLabels))
        # requires dplyr v.0.7+
        # the syntax `!!variablename:=` forces evaluation of the variablename before evaluating the rest of the function
    })
}

It works, and each iteration returns the entire data frame, with the relevant column (colname) changed to factor. But, each iteration overwrites the previous, so this function only returns the last result of i. How do I make sure that I end up with 1 single data frame, in which all the relevant columns are saved?

Sample data (make sure to comment out the first line of the function above, since we're defining t here):

 d <- data.frame("id" = sample(100:999, 10), "age" = sample(18:80, 10), "factor1" = c(rep("a", 3), rep("b", 3), rep("c", 4)), "factor2" = c("x","y","y","y","y","x","x","x","x","y"), stringsAsFactors = FALSE)
 t <- data.frame("Item" = c("factor1","factor2"), "Label" = c("This is factor 1", "This is factor 2"), "level1" = c("a","x"), "level2" = c("b","y"), "level3" = c("c","NA"))

Solution

If I understand correctly you have one data frame with factor column values of another data frame. You want to extract these from the 1st df and mutate these columns in the 2nd df and turn them into factors.

What about keeping a vector of the column names and then mutate them all?

colnames <- t %>%
  pull(Item) %>%
  as.character()

d_with_factors <- d %>%
  mutate_at(colnames, as.factor)

Then

sapply(d_with_factors, class)

Returns

       id       age   factor1   factor2 
"integer" "integer"  "factor"  "factor"