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[Experimental]

This is an experimental new function that allows you to modify the grouping variables for a single operation.

Usage

with_groups(.data, .groups, .f, ...)

Arguments

.data

A data frame

.groups

<tidy-select> One or more variables to group by. Unlike group_by(), you can only group by existing variables, and you can use tidy-select syntax like c(x, y, z) to select multiple variables.

Use NULL to temporarily ungroup.

.f

Function to apply to regrouped data. Supports purrr-style ~ syntax

...

Additional arguments passed on to ....

Examples

df <- tibble(g = c(1, 1, 2, 2, 3), x = runif(5))
df %>%
  with_groups(g, mutate, x_mean = mean(x))
#> # A tibble: 5 × 3
#>       g     x x_mean
#>   <dbl> <dbl>  <dbl>
#> 1     1 0.727  0.632
#> 2     1 0.537  0.632
#> 3     2 0.437  0.658
#> 4     2 0.879  0.658
#> 5     3 0.801  0.801
df %>%
  with_groups(g, ~ mutate(.x, x1 = first(x)))
#> # A tibble: 5 × 3
#>       g     x    x1
#>   <dbl> <dbl> <dbl>
#> 1     1 0.727 0.727
#> 2     1 0.537 0.727
#> 3     2 0.437 0.437
#> 4     2 0.879 0.437
#> 5     3 0.801 0.801

df %>%
  group_by(g) %>%
  with_groups(NULL, mutate, x_mean = mean(x))
#> # A tibble: 5 × 3
#> # Groups:   g [3]
#>       g     x x_mean
#>   <dbl> <dbl>  <dbl>
#> 1     1 0.727  0.676
#> 2     1 0.537  0.676
#> 3     2 0.437  0.676
#> 4     2 0.879  0.676
#> 5     3 0.801  0.676

# NB: grouping can't be restored if you remove the grouping variables
df %>%
  group_by(g) %>%
  with_groups(NULL, mutate, g = NULL)
#> # A tibble: 5 × 1
#>       x
#>   <dbl>
#> 1 0.727
#> 2 0.537
#> 3 0.437
#> 4 0.879
#> 5 0.801