group_nest: Nest a tibble using a grouping specification

In hadley/dplyr: A Grammar of Data Manipulation

Nest a tibble using a grouping specification

Description

Nest a tibble using a grouping specification

Usage

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.

Lifecycle

group_nest() is not stable because tidyr::nest(.by =) provides very similar behavior. It may be deprecated in the future.

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()

# 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()

#----- 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)

hadley/dplyr documentation built on Nov. 6, 2024, 4:48 p.m.