[Experimental]

Nest a tibble using a grouping specification

group_nest(.tbl, ..., .key = "data", keep = FALSE)

Arguments

.tbl

A tbl

...

Grouping specification, forwarded to group_by()

.key

the name of the list column

keep

Should the grouping columns be kept in the list column.

Value

A tbl with one row per unique combination of the grouping variables. The first columns are the grouping variables, followed by a list column of tibbles with matching rows of the remaining columns.

Grouped data frames

The primary use case for group_nest() is with already grouped data frames, typically a result of group_by(). In this case group_nest() only uses the first argument, the grouped tibble, and warns when ... is used.

Ungrouped data frames

When used on ungrouped data frames, group_nest() forwards the ... to group_by() before nesting, therefore the ... are subject to the data mask.

See also

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

Examples

#----- use case 1: a grouped data frame iris %>% group_by(Species) %>% group_nest()
#> # A tibble: 3 x 2 #> Species data #> <fct> <list<tibble[,4]>> #> 1 setosa [50 × 4] #> 2 versicolor [50 × 4] #> 3 virginica [50 × 4]
# this can be useful if the grouped data has been altered before nesting iris %>% group_by(Species) %>% filter(Sepal.Length > mean(Sepal.Length)) %>% group_nest()
#> # A tibble: 3 x 2 #> Species data #> <fct> <list<tibble[,4]>> #> 1 setosa [22 × 4] #> 2 versicolor [24 × 4] #> 3 virginica [22 × 4]
#----- use case 2: using group_nest() on a ungrouped data frame with # a grouping specification that uses the data mask starwars %>% group_nest(species, homeworld)
#> # A tibble: 58 x 3 #> species homeworld data #> <chr> <chr> <list<tibble[,12]>> #> 1 Aleena Aleen Minor [1 × 12] #> 2 Besalisk Ojom [1 × 12] #> 3 Cerean Cerea [1 × 12] #> 4 Chagrian Champala [1 × 12] #> 5 Clawdite Zolan [1 × 12] #> 6 Droid Naboo [1 × 12] #> 7 Droid Tatooine [2 × 12] #> 8 Droid NA [3 × 12] #> 9 Dug Malastare [1 × 12] #> 10 Ewok Endor [1 × 12] #> # … with 48 more rows