Understanding the positioning of c_across and across in functions

[Khundiman]

Hi

Would someone help me understand why across and c_across are positioned differently in functions. This knowledge will help me easily remember their positions so that I shouldn't be making mistakes in using the functions.

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
df <- tibble(id = 1:6, w = 10:15, x = 20:25, y = 30:35, z = 40:45)

df %>% 
  rowwise() %>%
  mutate(total = sum(c_across(w:z))) %>% 
  ungroup() %>% 
  mutate(across(w:z, ~ . / total))
#> # A tibble: 6 x 6
#>      id     w     x     y     z total
#>   <int> <dbl> <dbl> <dbl> <dbl> <int>
#> 1     1 0.1   0.2   0.3   0.4     100
#> 2     2 0.106 0.202 0.298 0.394   104
#> 3     3 0.111 0.204 0.296 0.389   108
#> 4     4 0.116 0.205 0.295 0.384   112
#> 5     5 0.121 0.207 0.293 0.379   116
#> 6     6 0.125 0.208 0.292 0.375   120

#why isn't the syntax for for c_across(w:x, sum)
#Be free to use any other example dataset that you are comfortable with

#Thanks

^{Created on 2021-02-09 by the reprex package (v0.3.0)}