Using functions of multiple columns in a dplyr mutate_at call

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This was answered by @eipi10 in @eipi10’s comment on the question, but I’m writing it here for posterity.

The solution here is to use:

df %>%
   mutate_at(.vars = vars(y, z),
             .funs = list(~ ifelse(x, ., NA)))

You can also use the new across() function with mutate(), like so:

df %>%
   mutate(across(c(y, z), ~ ifelse(x, ., NA)))

The use of the formula operator (as in ~ ifelse(...)) here indicates that ifelse(x, ., NA) is an anonymous function that is being defined within the call to mutate_at().

This works similarly to defining the function outside of the call to mutate_at(), like so:

temp_fn <- function(input) ifelse(test = df[["x"]],
                                  yes = input,
                                  no = NA)

df %>%
   mutate_at(.vars = vars(y, z),
             .funs = temp_fn)

Note on syntax changes in dplyr: Prior to dplyr version 0.8.0, you would simply write .funs = funs(ifelse(x, . , NA)), but the funs() function is being deprecated and will soon be removed from dplyr.

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