Mutating several columns with different functions simultaneously

Question

Consider the following table:

df <- tibble(
  col1 = sample(10:1000, 5),
  col2 = sample(1000:10000, 5),
  col3 = sample(100:500, 5)
)

I'd like to divide col1 and col3 by 10, and col2 by 1000.

I can do this by using 2 mutate_at functions like so:

df %>% 
  mutate_at(
    c("col1", "col3"),
    ~ .x / 10
  ) %>% 
  mutate_at(
    "col2",
    ~ .x / 1000
  )

Is there a way to do the above in a single mutate_x function?

In the next release of dplyr, you could use across and do this with one mutate. df %>% mutate(across(col1, col2), ~.x/10, across(col3), ~.x/1000) . See here tidyverse.org/blog/2020/04/dplyr-1-0-0-colwise — Ronak Shah
– Ronak Shah, Commented Apr 9, 2020 at 7:23

caldwellst · Accepted Answer · 2020-04-09 07:42:06Z

2

As Ronak says, across will replace the scoped verbs _at, _if, _all in the newest version of dplyr. You can start using it prior to its CRAN release by doing remotes::install_github("tidyverse/dplyr").

The correct use of across is slightly different than in his comment above.

df %>% mutate(across(c(col1, col2), ~.x/10), 
              across(col3, ~.x/1000))
#> # A tibble: 5 x 3
#>    col1  col2  col3
#>   <dbl> <dbl> <dbl>
#> 1  87.3  127. 0.324
#> 2  19.5  752. 0.194
#> 3  74.3  972. 0.197
#> 4  42.5  258. 0.116
#> 5  88.6  749. 0.11

answered Apr 9, 2020 at 7:42

caldwellst

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