Change multiple value labels using tidyverse syntax?

Question

The labelled package provides this functionality to modify value labels for multiple variables in one go:

df <- data.frame(v1 = 1:3, v2 = c(2, 3, 1), v3 = 3:1)
val_labels(df[, c("v1", "v3")]) <- c(YES = 1, MAYBE = 2, NO = 3)
val_labels(df)

But I'm wondering if there's a way to do this in tidyverse syntax:

Something like this:

library(tidyverse)
df%>%
mutate(across(V1:V2), ~val_labels(.x)<-c(YES = 1, MAYBE = 2, NO = 3)

Answer 1

We need to assign and then return the column (.x). In addition, when there are more than one expression, wrap it inside the {}

library(dplyr)
library(labelled)
df <- df %>%
  mutate(across(v1:v2, ~ 
       {
       val_labels(.x) <- c(YES = 1, MAYBE = 2, NO = 3)
       .x
     }))

-output

> val_labels(df)
$v1
  YES MAYBE    NO 
    1     2     3 

$v2
  YES MAYBE    NO 
    1     2     3 

$v3
NULL

Answer 2

I would suggest using haven's labelled class directly, alternatively check out the labelled package's functions made for the dplyr syntax, e.g. add_value_labels.

df <-
  df |>
  mutate(across(v1:v2,
                ~ haven::labelled(.,
                                  labels = c(YES   = 1,
                                             MAYBE = 2,
                                             NO    = 3)
                                  )
                )
         )

labelled::val_labels(df)

Output:

$v1
  YES MAYBE    NO 
    1     2     3 

$v2
  YES MAYBE    NO 
    1     2     3 

$v3
NULL

A side note: Unless you have a very specific reason for using the labelled-package I'd suggest that you keep the usage to a minimum and coerce into factors, especially in the case of value labels. I've learned the hard way that the labelled-package (and sjlabelled for that matter) will often let you do things that seems smart on the outset but isn't in the long run.

A labelled vector is a common data structure in other statistical environments, allowing you to assign text labels to specific values. (...) This class provides few methods, as I expect you'll coerce to a standard R class (e.g. a factor()) soon after importing.

https://haven.tidyverse.org/reference/labelled.html (My emphasis)