A couple of case_when() tricks | Alan Yeung

[utterances-bot]

A couple of case_when() tricks | Alan Yeung

Combining case_when() and across()
If you want to use case_when() and across() different variables, then here is an example that can do this with the help of the get() and cur_column() functions.
library(tidyverse)
iris_df <- as_tibble(iris) %>% mutate(flag_Petal.Length = as.integer(Petal.Length > 1.5),
flag_Petal.Width = as.integer(Petal.Width > 0.2))
iris_df %>% mutate(across(c(Petal.Length, Petal.Width),
~case_when(
get(glue::glue("flag_{cur_column()}")) == 1 ~ NA_real_,
TRUE ~ .x
))) %>% select(contains("Petal"))

# A tibble: 150 × 4

Petal.

https://alan-y.netlify.com/post/couple-of-casewhen-tricks/

[AjayKMehta]

You can use rlang like this:

iris_df %>% 
  mutate(across(c(Petal.Length, Petal.Width),
                ~ case_when(eval(rlang::sym(eval(paste0("flag_", cur_column())))) == 1 ~ NA_real_,
                            TRUE ~ .x))) %>% 
  select(contains("Petal"))