Summarise Each Group Down to One Row

Source: R/summarise2.R

Wrapper on dplyr::summarise that sets the default for the .group variable to "keep". This means that all the groups set in dplyr::group_by are retained, not just the first group.

summarise2(.data, ..., .by = NULL, .groups = "keep")

summarize2(.data, ..., .by = NULL, .groups = "keep")

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> Name-value pairs of summary functions. The name will be the name of the variable in the result.

The value can be:

  • A vector of length 1, e.g. min(x), n(), or sum(is.na(y)).

  • A data frame, to add multiple columns from a single expression.

[Deprecated] Returning values with size 0 or >1 was deprecated as of 1.1.0. Please use reframe() for this instead.

.by

[Experimental]

<tidy-select> Optionally, a selection of columns to group by for just this operation, functioning as an alternative to group_by(). For details and examples, see ?dplyr_by.

.groups

[Experimental] Grouping structure of the result.

  • "drop_last": dropping the last level of grouping. This was the only supported option before version 1.0.0.

  • "drop": All levels of grouping are dropped.

  • "keep": Same grouping structure as .data.

  • "rowwise": Each row is its own group.

When .groups is not specified, it is chosen based on the number of rows of the results:

  • If all the results have 1 row, you get "drop_last".

  • If the number of rows varies, you get "keep" (note that returning a variable number of rows was deprecated in favor of reframe(), which also unconditionally drops all levels of grouping).

In addition, a message informs you of that choice, unless the result is ungrouped, the option "dplyr.summarise.inform" is set to FALSE, or when summarise() is called from a function in a package.

Value

An object usually of the same type as .data.

  • The rows come from the underlying group_keys().

  • The columns are a combination of the grouping keys and the summary expressions that you provide.

  • The grouping structure is controlled by the .groups= argument, the output may be another grouped_df, a tibble or a rowwise data frame.

  • Data frame attributes are not preserved, because summarise() fundamentally creates a new data frame.

Useful functions

Backend variations

The data frame backend supports creating a variable and using it in the same summary. This means that previously created summary variables can be further transformed or combined within the summary, as in mutate(). However, it also means that summary variables with the same names as previous variables overwrite them, making those variables unavailable to later summary variables.

This behaviour may not be supported in other backends. To avoid unexpected results, consider using new names for your summary variables, especially when creating multiple summaries.

Methods

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

The following methods are currently available in loaded packages: no methods found .

Examples

 df <- data.frame(
  group = c("A", "A", "B", "B"), 
  id = c(1, 1, 2, 2), 
  value = c(10, 4, 20, 6)
 )
# summarise2 doesn't produce message about groups
df |> dplyr::group_by(group, id) |> summarise2(mean = mean(value))
#> # A tibble: 2 × 3
#> # Groups:   group, id [2]
#>   group    id  mean
#>   <chr> <dbl> <dbl>
#> 1 A         1     7
#> 2 B         2    13
# summarise doesn't retain all the groups set in `group_by`
df |> dplyr::group_by(group, id) |> dplyr::summarise(mean = mean(value))
#> `summarise()` has grouped output by 'group'. You can override using the
#> `.groups` argument.
#> # A tibble: 2 × 3
#> # Groups:   group [2]
#>   group    id  mean
#>   <chr> <dbl> <dbl>
#> 1 A         1     7
#> 2 B         2    13