group_dt: Data manipulation within groups

In hope-data-science/tidydt: Tidy Verbs for 'data.table'

Description

Analogous function for group_by in dplyr, but in another efficient way.

Usage

group_dt(data, by = NULL, ...)

Arguments

data	data.frame
by	Variables to group by,unquoted name of grouping variable of list of unquoted names of grouping variables.
...	Any data manipulation arguments that could be implemented on a data.frame.

Value

data.table

Examples

iris %>% group_dt(by = Species,slice_dt(1:2))
iris %>% group_dt(Species,filter_dt(Sepal.Length == max(Sepal.Length)))
iris %>% group_dt(Species,summarise_dt(new = max(Sepal.Length)))

# you can pipe in the `group_dt`
iris %>% group_dt(Species,
                  mutate_dt(max= max(Sepal.Length)) %>%
                    summarise_dt(sum=sum(Sepal.Length)))

# for summarise_dt, you can use "by" to calculate within the group
mtcars %>%
  summarise_dt(
   disp = mean(disp),
   hp = mean(hp),
   by = cyl
)

 # but you could also, of course, use group_dt
mtcars %>%
  group_dt(by =.(vs,am),
    summarise_dt(avg = mean(mpg)))

hope-data-science/tidydt documentation built on Feb. 21, 2020, 10:25 a.m.