These are methods for the dplyr group_map() and group_modify() generics.
They are both translated to [.data.table.
Usage
# S3 method for dtplyr_step
group_modify(.data, .f, ..., keep = FALSE)
# S3 method for dtplyr_step
group_map(.data, .f, ..., keep = FALSE)Arguments
- .data
- .f
The name of a two argument function. The first argument is passed
.SD,the data.table representing the current group; the second argument is passed.BY, a list giving the current values of the grouping variables. The function should return a list or data.table.- ...
Additional arguments passed to
.f- keep
Not supported for lazy_dt.
Value
group_map() applies .f to each group, returning a list.
group_modify() replaces each group with the results of .f, returning a
modified lazy_dt().
Examples
library(dplyr)
dt <- lazy_dt(mtcars)
dt %>%
group_by(cyl) %>%
group_modify(head, n = 2L)
#> Source: local data table [6 x 11]
#> Groups: cyl
#> Call: `_DT16`[, head(.SD, .BY, n = ~2L), by = .(cyl)]
#>
#> cyl mpg disp hp drat wt qsec vs am gear carb
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 6 21 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 6 21 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 4 22.8 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 4 24.4 147. 62 3.69 3.19 20 1 0 4 2
#> 5 8 18.7 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 8 14.3 360 245 3.21 3.57 15.8 0 0 3 4
#>
#> # Use as.data.table()/as.data.frame()/as_tibble() to access results
dt %>%
group_by(cyl) %>%
group_map(head, n = 2L)
#> [[1]]
#> mpg disp hp drat wt qsec vs am gear carb
#> 1: 21 160 110 3.9 2.620 16.46 0 1 4 4
#> 2: 21 160 110 3.9 2.875 17.02 0 1 4 4
#>
#> [[2]]
#> mpg disp hp drat wt qsec vs am gear carb
#> 1: 22.8 108.0 93 3.85 2.32 18.61 1 1 4 1
#> 2: 24.4 146.7 62 3.69 3.19 20.00 1 0 4 2
#>
#> [[3]]
#> mpg disp hp drat wt qsec vs am gear carb
#> 1: 18.7 360 175 3.15 3.44 17.02 0 0 3 2
#> 2: 14.3 360 245 3.21 3.57 15.84 0 0 3 4
#>