How do I change 0 values in numeric data type columns to NA, without changing FALSE operators in logical data type columns to NA?

I want to convert all 0 numerical values in a spreadsheet to NA. The code below changes all of my 0 values in numerical columns to NA as intended, however, FALSE values in logical columns are also being changed to NA.

dataframe <- na_if(dataframe, 0)

Is there a way around this that doesn’t require me splitting the data frame up into logical and numeric parts, converting 0s to NAs on the numeric data, then merging it? Thank you!

>Solution :

We may have to loop across numeric columns because TRUE/FALSE are otherwise 1/0 when coerced

library(dplyr)
FibreDatabase <- FibreDatabase %>%
    mutate(across(where(is.numeric), na_if, 0))

If we check the source code of na_if

...
 x[x == y] <- NA
...

which does the conversion

> df1 <- data.frame(v1 = FALSE, v2 = c(0, 1))
> df1 == 0
       v1    v2
[1,] TRUE  TRUE
[2,] TRUE FALSE

Here, the FALSE are also coerced to 0 and it returns TRUE when we do the == as below

> df1 %>%
    mutate(across(where(is.numeric), na_if, 0))
     v1 v2
1 FALSE NA
2 FALSE  1
> na_if(df1, 0)
  v1 v2
1 NA NA
2 NA  1