Count observations with totals row — count_with

This variant of dplyr::count() adds a row with column totals. Totals are computed for the first column passed to ... unless otherwise specified in totals_for.

Usage

count_with_total(
  .data,
  ...,
  totals_for = NULL,
  label = "Total",
  first_row = FALSE,
  wt = NULL,
  sort = FALSE,
  name = NULL,
  .drop = dplyr::group_by_drop_default()
)

Arguments

...

<data-masking> Variables to group by.

totals_for

The variable to total for. If omitted, defaults to the first variable in ....

label

The label for the totals row. Defaults to "Total".

first_row

If TRUE, the totals row will be placed first in the output. If FALSE (default), it will be placed last.

wt

<data-masking> Frequency weights. Can be NULL or a variable:

If NULL (the default), counts the number of rows in each group.
If a variable, computes sum(wt) for each group.

sort

If TRUE, will show the largest groups at the top.

name

The name of the new column in the output.

If omitted, it will default to n. If there's already a column called n, it will use nn. If there's a column called n and nn, it'll use nnn, and so on, adding ns until it gets a new name.

.drop

Handling of factor levels that don't appear in the data, passed on to dplyr::group_by(). If FALSE will include counts for empty groups (i.e. for levels of factors that don't exist in the data).

Value

A data frame with counts for each grouping level, along with a "totals" row with the column totals for the totaled variable.

Examples

mtcars %>%
  count_with_total(cyl)
#>     cyl  n
#> 1     4 11
#> 2     6  7
#> 3     8 14
#> 4 Total 32

mtcars %>%
  count_with_total(cyl, gear)
#>      cyl gear  n
#> 1      4    3  1
#> 2      4    4  8
#> 3      4    5  2
#> 4      6    3  2
#> 5      6    4  4
#> 6      6    5  1
#> 7      8    3 12
#> 8      8    5  2
#> 9  Total    3 15
#> 10 Total    4 12
#> 11 Total    5  5

mtcars %>%
  count_with_total(cyl, gear, totals_for = gear)
#>    cyl  gear  n
#> 1    4     3  1
#> 2    4     4  8
#> 3    4     5  2
#> 4    4 Total 11
#> 5    6     3  2
#> 6    6     4  4
#> 7    6     5  1
#> 8    6 Total  7
#> 9    8     3 12
#> 10   8     5  2
#> 11   8 Total 14