Combine values from multiple columns

Source: R/across.R

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.

c_across(cols = everything())

Arguments

cols

<tidy-select> Columns to transform. Because across() is used within functions like summarise() and mutate(), you can't select or compute upon grouping variables.

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 x 7
#> # Rowwise: 
#>      id      w     x     y        z   sum    sd
#>   <int>  <dbl> <dbl> <dbl>    <dbl> <dbl> <dbl>
#> 1     1 0.0349 0.315 0.516 0.000104 0.865 0.244
#> 2     2 0.439  0.856 0.869 0.205    2.37  0.326
#> 3     3 0.644  0.540 0.857 0.945    2.99  0.187
#> 4     4 0.995  0.873 0.346 0.281    2.50  0.363