group_by: Group by one or more variables

In tidybulk: Brings transcriptomics to the tidyverse

Description

Most data operations are done on groups defined by variables. 'group_by()' takes an existing tbl and converts it into a grouped tbl where operations are performed "by group". 'ungroup()' removes grouping.

Usage

group_by(.data, ..., .add = FALSE, .drop = group_by_drop_default(.data))

Arguments

.data	A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See *Methods*, below, for more details.
...	In 'group_by()', variables or computations to group by. In 'ungroup()', variables to remove from the grouping.
.add	When 'FALSE', the default, 'group_by()' will override existing groups. To add to the existing groups, use '.add = TRUE'. This argument was previously called 'add', but that prevented creating a new grouping variable called 'add', and conflicts with our naming conventions.
.drop	When '.drop = TRUE', empty groups are dropped. See [group_by_drop_default()] for what the default value is for this argument.

Value

A [grouped data frame][grouped_df()], unless the combination of '...' and 'add' yields a non empty set of grouping columns, a regular (ungrouped) data frame otherwise.

Methods

These function are **generic**s, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.

Methods available in currently loaded packages:

Examples

`%>%` = magrittr::`%>%`
by_cyl <- mtcars %>% group_by(cyl)

tidybulk documentation built on April 7, 2021, 6 p.m.