Groups a dataframe by columns specified in ... using dplyr::group_by(),
and adds an additional group containing all observations. Useful for
including a "total" or "overall" row in summaries.
If more than one column is passed to ..., the "total" group will combine
all groups in the first column passed, unless a different column is specified
in .totals_for.
Removing or changing the grouping structure after calling
group_with_total() but before aggregating may yield inaccurate results.
Usage
group_with_total(
.data,
...,
.totals_for = NULL,
.label = "Total",
.add = FALSE,
.drop = dplyr::group_by_drop_default(.data),
.first_row = FALSE
)Examples
ggplot2::mpg %>%
group_with_total(class) %>%
dplyr::summarize(n = dplyr::n(), cty = mean(cty), hwy = mean(hwy))
#> # A tibble: 8 × 4
#> class n cty hwy
#> <fct> <int> <dbl> <dbl>
#> 1 2seater 5 15.4 24.8
#> 2 compact 47 20.1 28.3
#> 3 midsize 41 18.8 27.3
#> 4 minivan 11 15.8 22.4
#> 5 pickup 33 13 16.9
#> 6 subcompact 35 20.4 28.1
#> 7 suv 62 13.5 18.1
#> 8 Total 234 16.9 23.4
ggplot2::mpg %>%
group_with_total(year, drv, .label = "all years") %>%
dplyr::summarize(n = dplyr::n(), cty = mean(cty), hwy = mean(hwy))
#> `summarise()` has grouped output by 'year'. You can override using the
#> `.groups` argument.
#> # A tibble: 9 × 5
#> # Groups: year [3]
#> year drv n cty hwy
#> <fct> <chr> <int> <dbl> <dbl>
#> 1 1999 4 49 14.2 18.8
#> 2 1999 f 57 20.0 27.9
#> 3 1999 r 11 14 20.6
#> 4 2008 4 54 14.4 19.5
#> 5 2008 f 49 20.0 28.4
#> 6 2008 r 14 14.1 21.3
#> 7 all years 4 103 14.3 19.2
#> 8 all years f 106 20.0 28.2
#> 9 all years r 25 14.1 21
ggplot2::mpg %>%
group_with_total(year, drv, .totals_for = drv) %>%
dplyr::summarize(n = dplyr::n(), cty = mean(cty), hwy = mean(hwy))
#> `summarise()` has grouped output by 'year'. You can override using the
#> `.groups` argument.
#> # A tibble: 8 × 5
#> # Groups: year [2]
#> year drv n cty hwy
#> <int> <fct> <int> <dbl> <dbl>
#> 1 1999 4 49 14.2 18.8
#> 2 1999 f 57 20.0 27.9
#> 3 1999 r 11 14 20.6
#> 4 1999 Total 117 17.0 23.4
#> 5 2008 4 54 14.4 19.5
#> 6 2008 f 49 20.0 28.4
#> 7 2008 r 14 14.1 21.3
#> 8 2008 Total 117 16.7 23.5