Replacing different values with missing in a subset of columns

where-is-imap_at.R

library(tidyverse)

mt_tbl <- as_tibble(mtcars)

# types need to match those in mtcars (all doubles)
# careful; `na_if` doesn't work with multiple values
missing_codes <- list(
  cyl = 6.0,
  disp = 160.0,
  carb = 1.0
)

# no iteration; baseline result
result_naive <- mt_tbl %>%
  mutate(
    cyl  = na_if(cyl,  missing_codes$cyl),
    disp = na_if(disp, missing_codes$disp),
    carb = na_if(carb, missing_codes$carb)
  )

result_naive


# for loop
result_forloop <- mt_tbl
for (col in names(missing_codes)) {
  result_forloop[[col]] <- na_if(result_forloop[[col]], missing_codes[[col]])
}

all_equal(result_naive, result_forloop)


# functional-ish
result_functionalish <- mt_tbl
result_functionalish[names(missing_codes)] <- imap(
  result_functionalish[names(missing_codes)],
  ~ na_if(.x, missing_codes[[.y]])
)

all_equal(result_functionalish, result_naive)


# more functional, maybe
helper <- function(col, name, lookup) {
  if (name %in% names(lookup)) {
    col <- na_if(col, lookup[[name]])
  }
  col
}

result_functional <- imap_dfc(mt_tbl, helper, missing_codes)

all_equal(result_functional, result_naive)