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Information about the "current" group or variable

Source: R/context.R
context.Rd

These functions return information about the "current" group or "current" variable, so only work inside specific contexts like summarise() and mutate().

  • n() gives the current group size.

  • cur_group() gives the group keys, a tibble with one row and one column for each grouping variable.

  • cur_group_id() gives a unique numeric identifier for the current group.

  • cur_group_rows() gives the row indices for the current group.

  • cur_column() gives the name of the current column (in across() only).

See group_data() for equivalent functions that return values for all groups.

See pick() for a way to select a subset of columns using tidyselect syntax while inside summarise() or mutate().

Usage

n()

cur_group()

cur_group_id()

cur_group_rows()

cur_column()

data.table

If you're familiar with data.table:

  • cur_group_id() <-> .GRP

  • cur_group() <-> .BY

  • cur_group_rows() <-> .I

See pick() for an equivalent to .SD.

Examples

df <- tibble(
  g = sample(rep(letters[1:3], 1:3)),
  x = runif(6),
  y = runif(6)
)
gf <- df %>% group_by(g)

gf %>% summarise(n = n())
#> # A tibble: 3 × 2
#>   g         n
#>   <chr> <int>
#> 1 a         1
#> 2 b         2
#> 3 c         3

gf %>% mutate(id = cur_group_id())
#> # A tibble: 6 × 4
#> # Groups:   g [3]
#>   g         x     y    id
#>   <chr> <dbl> <dbl> <int>
#> 1 b     0.549 0.776     2
#> 2 c     0.486 0.584     3
#> 3 b     0.692 0.153     2
#> 4 c     0.524 0.604     3
#> 5 a     0.474 0.174     1
#> 6 c     0.828 0.118     3
gf %>% reframe(row = cur_group_rows())
#> # A tibble: 6 × 2
#>   g       row
#>   <chr> <int>
#> 1 a         5
#> 2 b         1
#> 3 b         3
#> 4 c         2
#> 5 c         4
#> 6 c         6
gf %>% summarise(data = list(cur_group()))
#> # A tibble: 3 × 2
#>   g     data            
#>   <chr> <list>          
#> 1 a     <tibble [1 × 1]>
#> 2 b     <tibble [1 × 1]>
#> 3 c     <tibble [1 × 1]>

gf %>% mutate(across(everything(), ~ paste(cur_column(), round(.x, 2))))
#> # A tibble: 6 × 3
#> # Groups:   g [3]
#>   g     x      y     
#>   <chr> <chr>  <chr> 
#> 1 b     x 0.55 y 0.78
#> 2 c     x 0.49 y 0.58
#> 3 b     x 0.69 y 0.15
#> 4 c     x 0.52 y 0.6 
#> 5 a     x 0.47 y 0.17
#> 6 c     x 0.83 y 0.12