How to use count for multiple column counts in one run

Usually, when I count a column in a data frame, I use the count() function from the dplyr package.

library(dplyr)

mtcars %>% 
  count(cyl)

and

mtcars %>% 
  count(am)

and

mtcars %>% 
  count(gear)

etc... Now I would like to count cyl, am, gear in one run.

Note: I don't mean

mtcars %>%
 count(cyl, am, gear)

My working approach so far:


library(dplyr)
library(tidyr)

mtcars %>% 
  count(am) %>% 
bind_rows(mtcars %>% 
            count(cyl)) %>% 
  bind_rows(mtcars %>% 
              count(gear)) %>% 
pivot_longer(-n, 
             values_drop_na = TRUE) %>% 
  unite("variable", c("name", "value")) %>% 
  relocate(variable, n)

  variable     n
  <chr>    <int>
1 am_0        19
2 am_1        13
3 cyl_4       11
4 cyl_6        7
5 cyl_8       14
6 gear_3      15
7 gear_4      12
8 gear_5       5

I'm wondering if there's a more concise way to achieve this.

Solution

Perhaps pivot and count?

library(dplyr)
library(tidyr) # pivot_longer
select(mtcars, am, cyl, gear) |>
  pivot_longer(cols = everything()) |>
  count(name, value)
# # A tibble: 8 × 3
#   name  value     n
#   <chr> <dbl> <int>
# 1 am        0    19
# 2 am        1    13
# 3 cyl       4    11
# 4 cyl       6     7
# 5 cyl       8    14
# 6 gear      3    15
# 7 gear      4    12
# 8 gear      5     5

You can "clean up" the names if you want by pasting them together.