Else clause of ifelse() not executing

October 8, 2024

In this MRE, I want to create a third group called age_group, and for all remaining values that do not meet the conditions, to be the actual age. Even if I make age a string (‘age’), the age_group variable does not replace these values with "age". What’s going on here?

new_df = df%>%
  mutate(age_group = ifelse(
             age %in% c(0:35), '0 to 35 years', ifelse(
               age_options=='-66', 'Prefer not to answer', ifelse(
                 age_options =='-99', 'Missing', age))
             )
           )

data

df = structure(list(age = c(NA, NA, 38, 33, 35, 44, 33, 26, 51, 42
), age_options = c(-99, -99, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, 
                                                                             -10L), class = c("tbl_df", "tbl", "data.frame"))

>Solution :

When you test age_options == '-66' on NA input in ifelse, the output is NA, instead of FALSE, so it doesn’t send us to the following test(s). So you need to deal with NA’s in the age_options variable first, e.g.

df%>%
  mutate(age_group = ifelse(
    age %in% c(0:35), '0 to 35 years', ifelse(
      is.na(age_options), age, ifelse(
        age_options=='-66', 'Prefer not to answer', ifelse(
          age_options =='-99', 'Missing', age)))))

This would be clearer using case_when, which is cleaner to read and doesn’t have the same issue with propagating NAs: case_when gives the specified output when the test is TRUE, instead of when it is TRUE or NA. One adjustment, though, is that with if_else or case_when, we need to intentionally coerce the output types to be consistent, i.e. all character. See here.

df%>%
  mutate(age_group = case_when(
    age %in% c(0:35) ~ '0 to 35 years',
    age_options=='-66' ~ 'Prefer not to answer',
    age_options=='-99' ~ 'Missing',
    .default = as.character(age)))

     age age_options age_group    
   <dbl>       <dbl> <chr>        
 1    NA         -99 Missing      
 2    NA         -99 Missing      
 3    38          NA 38           
 4    33          NA 0 to 35 years
 5    35          NA 0 to 35 years
 6    44          NA 44           
 7    33          NA 0 to 35 years
 8    26          NA 0 to 35 years
 9    51          NA 51           
10    42          NA 42