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

I'd also add that if_else() can attribute a value in case of NA, which is a handy way of adding an extra condition.

df <- data_frame(val = c(80, 90, NA, 110))
df %>% mutate(category = if_else(val < 100, 1, 2, missing = 9))

#     val category
#       
# 1    80        1
# 2    90        1
# 3    NA        9
# 4   110        2