tidyseurat (version 0.8.10)

group_by: Group by one or more variables

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

# S3 method for Seurat
group_by(.data, ..., .add = FALSE, .drop = group_by_drop_default(.data))

Value

A grouped data frame with class grouped_df, unless the combination of ... and add yields a empty set of grouping columns, in which case a tibble will be returned.

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.

...

<data-masking> In group_by(), variables or computations to group by. Computations are always done on the ungrouped data frame. To perform computations on the grouped data, you need to use a separate mutate() step before the group_by(). Computations are not allowed in nest_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.

.drop

Drop groups formed by factor levels that don't appear in the data? The default is TRUE except when .data has been previously grouped with .drop = FALSE. See group_by_drop_default() for details.

Methods

These function are generics, 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:

• group_by(): dplyr:::methods_rd("group_by").

• ungroup(): dplyr:::methods_rd("ungroup").

Ordering

Currently, group_by() internally orders the groups in ascending order. This results in ordered output from functions that aggregate groups, such as summarise().

When used as grouping columns, character vectors are ordered in the C locale for performance and reproducibility across R sessions. If the resulting ordering of your grouped operation matters and is dependent on the locale, you should follow up the grouped operation with an explicit call to arrange() and set the .locale argument. For example:

data |>
  group_by(chr) |>
  summarise(avg = mean(x)) |>
  arrange(chr, .locale = "en")

This is often useful as a preliminary step before generating content intended for humans, such as an HTML table.

Legacy behavior

Prior to dplyr 1.1.0, character vector grouping columns were ordered in the system locale. Setting the global option dplyr.legacy_locale to TRUE retains this legacy behavior, but this has been deprecated. Update existing code to explicitly call arrange(.locale = ) instead. Run Sys.getlocale("LC_COLLATE") to determine your system locale, and compare that against the list in stringi::stri_locale_list() to find an appropriate value for .locale, i.e. for American English, "en_US".

See Also

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

Examples

data("pbmc_small")
pbmc_small |>  group_by(groups)