Converting multiple columns to factors and releveling with mutate(across)-CodePudding

dat <- data.frame(Comp1Letter = c("A", "B", "D", "F", "U", "A*", "B", "C"),
                   Comp2Letter = c("B", "C", "E", "U", "A", "C", "A*", "E"),
                   Comp3Letter = c("D", "A", "C", "D", "F", "D", "C", "A"))  

GradeLevels <- c("A*", "A", "B", "C", "D", "E", "F", "G", "U")

I have a dataframe that looks something like the above (but with many other columns I don't want to change).

The columns I am interested in changing contains lists of letter grades, but are currently character vectors and not in the right order.

I need to convert each of these columns into factors with the correct order. I've been able to get this to work using the code below:

factordat <-
    dat %>%
      mutate(Comp1Letter = factor(Comp1Letter, levels = GradeLevels)) %>%
      mutate(Comp2Letter = factor(Comp2Letter, levels = GradeLevels)) %>%
      mutate(Comp3Letter = factor(Comp3Letter, levels = GradeLevels))

However this is super verbose and chews up a lot of space.

Looking at some other questions, I've tried to use a combination of mutate() and across(), as seen below:

factordat <-
  dat %>%
    mutate(across(c(Comp1Letter, Comp2Letter, Comp3Letter) , factor(levels = GradeLetters)))

However when I do this the vectors remain character vectors.

Could someone please tell me what I'm doing wrong or offer another option?

CodePudding user response：

You can do across as an anonymous function like this:

dat <- data.frame(Comp1Letter = c("A", "B", "D", "F", "U", "A*", "B", "C"),
                   Comp2Letter = c("B", "C", "E", "U", "A", "C", "A*", "E"),
                   Comp3Letter = c("D", "A", "C", "D", "F", "D", "C", "A"))  

GradeLevels <- c("A*", "A", "B", "C", "D", "E", "F", "G", "U")

dat %>%
  tibble::as_tibble() %>%
    dplyr::mutate(dplyr::across(c(Comp1Letter, Comp2Letter, Comp3Letter) , ~forcats::parse_factor(., levels = GradeLevels)))

# # A tibble: 8 × 3
#   Comp1Letter Comp2Letter Comp3Letter
#   <fct>       <fct>       <fct>      
# 1 A           B           D          
# 2 B           C           A          
# 3 D           E           C          
# 4 F           U           D          
# 5 U           A           F          
# 6 A*          C           D          
# 7 B           A*          C          
# 8 C           E           A

You were close, all that was left to be done was make the factor function anonymous. That can be done either with ~ and . in tidyverse or function(x) and x in base R.