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markfairbanks avatar markfairbanks commented on August 20, 2024

Well that's not always the case as it's evaluate both outcomes.

Yep you're right, it isn't the same in this case. This is also how dplyr::if_else() works.

What I don't understand is that there is no function ifelse in tidytable, R interprets ifelse as if_else I think because of the usage of tidytable::mutate.

Yes this is a semi-hidden feature of tidytable - it automatically substitutes in the faster tidytable::if_else().

Is there another way to avoid that behavior without adding base:: in front of every ifelse in my code?

As you found, the best way to escape this behavior is to namespace the function using base::ifelse(). If that's too much typing you can always do something like creating your own function with a slightly different name. I used my_ifelse() in this example but you could name it anything you want.

library(tidytable)

df <- tidytable(x = 1:3)

my_ifelse <- function(...) {
  ifelse(...)
}

df %>%
  mutate(x_check = my_ifelse(x >= 1, "x", stop("condition not met")))
#> # A tidytable: 3 × 2
#>       x x_check
#>   <int> <chr>  
#> 1     1 x      
#> 2     2 x      
#> 3     3 x

Hope this helps! If you have any questions please let me know.

from tidytable.

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