Summarize each group down to one row

summarize() returns one row for each combination of grouping variables (one difference with dplyr::summarize() is that summarize() only accepts grouped data). 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 'RPolarsDataFrame'
summarize(.data, ..., .by = NULL)

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

# S3 method for class 'RPolarsLazyFrame'
summarize(.data, ..., .by = NULL)

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

Arguments

.data

A Polars Data/LazyFrame

...

Name-value pairs. The name gives the name of the column in the output. The value can be:

• A vector the same length as the current group (or the whole data frame if ungrouped).

• NULL, to remove the column.

across() is mostly supported, except in a few cases. In particular, if the .cols argument is where(...), it will not select variables that were created before across(). Other select helpers are supported. See the examples.

.by

Optionally, a selection of columns to group by for just this operation, functioning as an alternative to group_by(). The group order is not maintained, use group_by() if you want more control over it.

Examples

mtcars |>
  as_polars_df() |>
  group_by(cyl) |>
  summarize(m_gear = mean(gear), sd_gear = sd(gear))
#> shape: (3, 3)
#> ┌─────┬──────────┬──────────┐
#> │ cyl ┆ m_gear   ┆ sd_gear  │
#> │ --- ┆ ---      ┆ ---      │
#> │ f64 ┆ f64      ┆ f64      │
#> ╞═════╪══════════╪══════════╡
#> │ 4.0 ┆ 4.090909 ┆ 0.53936  │
#> │ 8.0 ┆ 3.285714 ┆ 0.726273 │
#> │ 6.0 ┆ 3.857143 ┆ 0.690066 │
#> └─────┴──────────┴──────────┘
#> Groups [3]: cyl
#> Maintain order: FALSE

# an alternative syntax is to use `.by`
mtcars |>
  as_polars_df() |>
  summarize(m_gear = mean(gear), sd_gear = sd(gear), .by = cyl)
#> shape: (3, 3)
#> ┌─────┬──────────┬──────────┐
#> │ cyl ┆ m_gear   ┆ sd_gear  │
#> │ --- ┆ ---      ┆ ---      │
#> │ f64 ┆ f64      ┆ f64      │
#> ╞═════╪══════════╪══════════╡
#> │ 8.0 ┆ 3.285714 ┆ 0.726273 │
#> │ 6.0 ┆ 3.857143 ┆ 0.690066 │
#> │ 4.0 ┆ 4.090909 ┆ 0.53936  │
#> └─────┴──────────┴──────────┘