if statement - dplyr if_else() vs base R ifelse()

Question

I am fairly proficient within the Tidyverse, but have always used ifelse() instead of dplyr if_else(). I want to switch this behavior and default to always using dplyr::if_else() and deprecating ifelse() from my code.

Is there any reason not to do this? Would this likely get me into trouble? I'll spare you the details, but recently, not using if_else() screwed me up, when I unknowingly created a column of character matrices in my data analysis. If I switch to always using if_else() I hope to avoid this issue in the future.

Answer 1

if_else is more strict. It checks that both alternatives are of the same type and otherwise throws an error, while ifelse will promote types as necessary. This may be a benefit in some circumstances, but may otherwise break scripts if you don't check for errors or explicitly force type conversion. For example:

ifelse(c(TRUE,TRUE,FALSE),"a",3)
[1] "a" "a" "3"
if_else(c(TRUE,TRUE,FALSE),"a",3)
Error: `false` must be type character, not double