How to dynamically pass columns in tidyverse's across-CodePudding

Assuming the following data:

df <- data.frame(id     = 1:3,
                 result1 = 4:6,
                 result2 = letters[7:9],
                 result1_label = "test label 1",
                 result2_label = "test label 2")

I now want to create a rowwise(!) list column where I put together result1 with result1_label, and the same for result2.

Now, I can use tidyverse's across to "loop" through my results columns. However, I don't know how I could pass dynamically the respective label.

Here's my idea:

library(tidyverse)
df_new <- df %>%
  rowwise() %>%
  mutate(across(c(result1, result2), ~list(list("answer" = .,
                                                "label"  = sym(paste0(cur_column(),"_label")))),
                .names = "question_{.col}"))

It creates the columns I wanted. However, if you look at the data more closely with, you'll see that it didn't write the actual value from the result1_label column, but instead "symbol result1_label":

str(df_new$question_result1)

    tibble [3 x 1] (S3: rowwise_df/tbl_df/tbl/data.frame)
 $ question_result1:List of 3
  ..$ :List of 2
  .. ..$ answer: int 4
  .. ..$ label : symbol result1_label
  ..$ :List of 2
  .. ..$ answer: int 5
  .. ..$ label : symbol result1_label
  ..$ :List of 2
  .. ..$ answer: int 6
  .. ..$ label : symbol result1_label

Any idea, how I can pass teh actual value for the respective label column?

Note, my real-life example might have hundred or so such columns, that's why I need to automate.

I initially though I'd just pivot_longer my data so that I have one colum for the result and one for the label, but this doesn't work since the respective results columns have different classes (numeric and character).

CodePudding user response：

Use get:

df_new <- df %>%
  rowwise() %>%
  mutate(across(c(result1, result2), ~list(list("answer" = .,
                                                "label"  = get(paste0(cur_column(),"_label")))),
                .names = "question_{.col}"))

> str(df_new$question_result1)
List of 3
 $ :List of 2
  ..$ answer: int 4
  ..$ label : chr "test label 1"
 $ :List of 2
  ..$ answer: int 5
  ..$ label : chr "test label 1"
 $ :List of 2
  ..$ answer: int 6
  ..$ label : chr "test label 1"