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 0.240 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