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.
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()
ormutate()
).
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 0.126 0.533 0.172 0.196 1.03 0.186
#> 2 2 0.938 0.547 0.691 0.969 3.14 0.202
#> 3 3 0.801 0.0959 0.675 0.387 1.96 0.315
#> 4 4 0.758 0.388 0.946 0.650 2.74 0.233