[Experimental] Drop unused levels of all factors that are used as grouping variables, then recalculates the grouping structure.

group_trim() is particularly useful after a filter() that is intended to select a subset of groups.

group_trim(.tbl, .drop = group_by_drop_default(.tbl))

Arguments

.tbl

A grouped data frame

.drop

See group_by()

Value

A grouped data frame

See also

Other grouping functions: group_by(), group_map(), group_nest(), group_split()

Examples

iris %>% group_by(Species) %>% filter(Species == "setosa", .preserve = TRUE) %>% group_trim()
#> # A tibble: 50 x 5 #> # Groups: Species [1] #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> <dbl> <dbl> <dbl> <dbl> <fct> #> 1 5.1 3.5 1.4 0.2 setosa #> 2 4.9 3 1.4 0.2 setosa #> 3 4.7 3.2 1.3 0.2 setosa #> 4 4.6 3.1 1.5 0.2 setosa #> 5 5 3.6 1.4 0.2 setosa #> 6 5.4 3.9 1.7 0.4 setosa #> 7 4.6 3.4 1.4 0.3 setosa #> 8 5 3.4 1.5 0.2 setosa #> 9 4.4 2.9 1.4 0.2 setosa #> 10 4.9 3.1 1.5 0.1 setosa #> # … with 40 more rows