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c_across() is designed to work with rowwise() to make it easy to perform row-wise aggregations. It has two differences from c():

  • It uses tidy select semantics so you can easily select multiple variables. See vignette("rowwise") for more details.

  • It uses vctrs::vec_c() in order to give safer outputs.

Usage

c_across(cols)

Arguments

cols

<tidy-select> Columns to transform. You can't select grouping columns because they are already automatically handled by the verb (i.e. summarise() or mutate()).

See also

across() for a function that returns a tibble.

Examples

df <- tibble(id = 1:4, w = runif(4), x = runif(4), y = runif(4), z = runif(4))
df %>%
  rowwise() %>%
  mutate(
    sum = sum(c_across(w:z)),
    sd = sd(c_across(w:z))
  )
#> # A tibble: 4 × 7
#> # Rowwise: 
#>      id     w     x      y     z   sum    sd
#>   <int> <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl>
#> 1     1 0.240 0.438 0.0733 0.569  1.32 0.218
#> 2     2 0.564 0.505 0.190  0.126  1.38 0.220
#> 3     3 0.482 0.674 0.250  0.912  2.32 0.281
#> 4     4 0.184 0.792 0.162  0.213  1.35 0.303