These functions give information about the "current" group.
cur_data() gives the current data for the current group
cur_column() gives the name of the current column (for use in across() only)
cur_group_id() gives a group identification number
cur_group_rows() gives the row indices for each group
Can be used inside summarize(), mutate(), & filter()
cur_column()
cur_data()
cur_group_id()
cur_group_rows()df <- data.table(
x = 1:5,
y = c("a", "a", "a", "b", "b")
)
df %>%
mutate(
across(c(x, y), ~ paste(cur_column(), .x))
)
#> # A tidytable: 5 × 2
#> x y
#> <chr> <chr>
#> 1 x 1 y a
#> 2 x 2 y a
#> 3 x 3 y a
#> 4 x 4 y b
#> 5 x 5 y b
df %>%
summarize(data = list(cur_data()),
.by = y)
#> # A tidytable: 2 × 2
#> y data
#> <chr> <list>
#> 1 a <tidytable [3 × 1]>
#> 2 b <tidytable [2 × 1]>
df %>%
mutate(group_id = cur_group_id(),
.by = y)
#> # A tidytable: 5 × 3
#> x y group_id
#> <int> <chr> <int>
#> 1 1 a 1
#> 2 2 a 1
#> 3 3 a 1
#> 4 4 b 2
#> 5 5 b 2
df %>%
mutate(group_rows = cur_group_rows(),
.by = y)
#> # A tidytable: 5 × 3
#> x y group_rows
#> <int> <chr> <int>
#> 1 1 a 1
#> 2 2 a 2
#> 3 3 a 3
#> 4 4 b 1
#> 5 5 b 2