Avoiding type conflicts with dplyr::case_when

Question

I am trying to use dplyr::case_when within dplyr::mutate to create a new variable where I set some values to missing and recode other values simult

Answer 1

Try this ?

df %>% dplyr::mutate(new = dplyr::case_when(.$old == 1 ~ 5,
                                                  .$old == 2 ~ NA_real_,
                                                  TRUE~.$old))

> df
  old new
1   1   5
2   2  NA
3   3   3

Answer 2

As said in ?case_when:

All RHSs must evaluate to the same type of vector.

You actually have two possibilities:

1) Create new as a numeric vector

df <- df %>% mutate(new = case_when(old == 1 ~ 5,
                                    old == 2 ~ NA_real_,
                                    TRUE ~ as.numeric(old)))

Note that NA_real_ is the numeric version of NA, and that you must convert old to numeric because you created it as an integer in your original dataframe.

You get:

str(df)
# 'data.frame': 3 obs. of  2 variables:
# $ old: int  1 2 3
# $ new: num  5 NA 3

2) Create new as an integer vector

df <- df %>% mutate(new = case_when(old == 1 ~ 5L,
                                    old == 2 ~ NA_integer_,
                                    TRUE ~ old))

Here, 5L forces 5 into the integer type, and NA_integer_ is the integer version of NA.

So this time new is integer:

str(df)
# 'data.frame': 3 obs. of  2 variables:
# $ old: int  1 2 3
# $ new: int  5 NA 3