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Summarise each group down to one row

Source: R/summarise-rd.R, R/summarise.R
summarise.duckplyr_df.Rd

This is a method for the dplyr::summarise() generic. See "Fallbacks" section for differences in implementation. summarise() creates a new data frame. It returns one row for each combination of grouping variables; if there are no grouping variables, the output will have a single row summarising all observations in the input. It will contain one column for each grouping variable and one column for each of the summary statistics that you have specified.

Usage

# S3 method for class 'duckplyr_df'
summarise(.data, ..., .by = NULL, .groups = NULL)

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 with 1 row, to add multiple columns from a single expression.

.by

<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": drops 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 set to "drop_last" for a grouped data frame, and "keep" for a rowwise data frame. In addition, a message informs you of how the result will be grouped 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.

Fallbacks

There is no DuckDB translation in summarise.duckplyr_df()

  • with .groups = "rowwise".

These features fall back to dplyr::summarise(), see vignette("fallback") for details.

See also

dplyr::summarise()

Examples

library(duckplyr)
summarise(mtcars, mean = mean(disp), n = n())
#>       mean  n
#> 1 230.7219 32