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 t

Answer 1

Another reason to choose if_else over ifelse is that ifelse turns Date into numeric objects

Dates <- as.Date(c('2018-10-01', '2018-10-02', '2018-10-03'))
new_Dates <- ifelse(Dates == '2018-10-02', Dates + 1, Dates)
str(new_Dates)

#>  num [1:3] 17805 17807 17807

if_else is also faster than ifelse.

Note that when testing multiple conditions, the code would be more readable and less error-prone if we use case_when.

library(dplyr)

case_when(
  Dates == '2018-10-01' ~ Dates - 1,
  Dates == '2018-10-02' ~ Dates + 1,
  Dates == '2018-10-03' ~ Dates + 2,
  TRUE ~ Dates
)

#> [1] "2018-09-30" "2018-10-03" "2018-10-05"

Created on 2018-06-01 by the reprex package (v0.2.0).