I would like to use a combination of mutate, across, and case_when to set some cases to NA (missing) across multiple variables.
Say I have an indicator variable "vs" flagging cases that should be NA for variables "carb" and "gear". I would like to use something like this to set those cases to missing on both those variables at once:
data(mtcars) #load mtcars data
mtcars$carb <- as.integer(mtcars$carb) #set to integer, for purposes of illustration
mtcars <- mtcars %>%
mutate(across(c(gear:carb), ~ case_when(vs==1~NA,
T~.)))
I would like this to change "gear" and "carb" to NA for all cases for which "vs" is equal to 1. However, since carb is an integer and gear is numeric, I run into a type conflict:
Error: Problem with `mutate()` input `..1`.
ℹ `..1 = across(c(gear:carb), ~case_when(vs == 1 ~ NA, T ~ .))`.
x must be a logical vector, not a double vector.
If I were using mutate on each variable individually, I would replace NA with NA_integer_ for carb and NA with NA_real_ for gear. I can't do that here, since the variables contain different types of data.
Is there any way around this, or can I only use mutate(across()) like this with variables of the same type?
Thank you!
Another option would be to use an if
statement:
library(dplyr)
mtcars$carb <- as.integer(mtcars$carb)
mtcars <- mtcars %>%
mutate(across(c(gear:carb), ~ case_when(
vs == 1 ~ if (is.integer(.)) NA_integer_ else NA_real_,
T ~ .
)))
But the much more clever approach I learned thanks to the comment by @r2evans would be use .[NA]
which "will always give the appropriate NA
type":
mtcars <- mtcars %>%
mutate(across(c(gear:carb), ~ case_when(
vs == 1 ~ .[NA],
T ~ .
)))
head(mtcars)
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 NA NA
#> Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 NA NA
#> Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
#> Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 NA NA
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