[SOLVED] How to automate adding factors to variables in large data frame in R

Issue

I have a large data frame in R with over 200 mostly character variables that I would like to add factors for. I have prepared all levels and labels in an separate data frame. For a certain variable Var1, the corresponding levels and labels are Var1_v and Var1_b, for example for the variable Gender the levels and labels are named Gender_v and Gender_l.

Here is an example of my data:

df <- data.frame (Gender = c("2","2","1","2"),
                  AgeG = c("3","1","4","2"))

fct <- data.frame (Gender_v  = c("1", "2"),
                  Gender_b = c("Male", "Female"),
                  AgeG_v = c("1","2","3","4"),
                  AgeG_b = c("<25","25-60","65-80",">80"))

df$Gender <- factor(df$Gender, levels = fct$Gender_v, labels = fct$Gender_b, exclude = NULL)
df$AgeG <- factor(df$AgeG, levels = fct$AgeG_v, labels = fct$AgeG_b, exclude = NULL)

Is there away to automatize the process, so that the factors (levels and labels) are applied to corresponding variables without having me doing every single one individually?
I think it’s done through a function probebly with pmap.

My goal is minimize the effort needed for this process. Is there a better way to prepare the labels and levels as well?

Help is much appreciated.

Solution

A data frame is not really an appropriate data structure for storing the
factor level definitions in: there’s no reason to expect all factors to have
an equal amount of levels. Rather, I’d just use a plain list, and store the
level information more compactly as named vectors, along these lines:

df <- data.frame(
  Gender = c("2", "2", "1", "2"),
  AgeG = c("3", "1", "4", "2")
)

value_labels <- list(
  Gender = c("Male" = 1, "Female" = 2),
  AgeG = c("<25" = 1, "25-60" = 2, "65-80" = 3, ">80" = 4)
)

Then you can make a function that uses that data structure to make factors
in a data frame:

make_factors <- function(data, value_labels) {
  for (var in names(value_labels)) {
    if (var %in% colnames(data)) {
      vl <- value_labels[[var]]
      data[[var]] <- factor(
        data[[var]],
        levels = unname(vl),
        labels = names(vl)
      )
    }
  }
  data
}

make_factors(df, value_labels)
#>   Gender  AgeG
#> 1 Female 65-80
#> 2 Female   <25
#> 3   Male   >80
#> 4 Female 25-60

Answered By – Mikko Marttila

Answer Checked By – Pedro (BugsFixing Volunteer)