Interface GroupBy

Use multiple aggregations on columns. This can be combined with complete lazy API and is considered idiomatic polars.

Example

// use lazy api rest parameter style
> df.groupBy('foo', 'bar')
>   .agg(pl.sum('ham'), col('spam').tail(4).sum())

// use lazy api array style
> df.groupBy('foo', 'bar')
>   .agg([pl.sum('ham'), col('spam').tail(4).sum()])

// use a mapping
> df.groupBy('foo', 'bar')
>   .agg({'spam': ['sum', 'min']})

Copy

Aggregate the groups into Series.

Count the number of values in each group.

Deprecated

Since

0.10.0

Use

len

Aggregate the first values in the group.

Return a DataFrame with:

• the groupby keys
• the group indexes aggregated as lists

Return first n rows of each group.

Example

> df = pl.DataFrame({
>   "letters": ["c", "c", "a", "c", "a", "b"],
>   "nrs": [1, 2, 3, 4, 5, 6]
> })
> df
shape: (6, 2)
╭─────────┬─────╮
│ letters ┆ nrs │
│ ---     ┆ --- │
│ str     ┆ i64 │
╞═════════╪═════╡
│ "c"     ┆ 1   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "c"     ┆ 2   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "a"     ┆ 3   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "c"     ┆ 4   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "a"     ┆ 5   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "b"     ┆ 6   │
╰─────────┴─────╯
> df.groupby("letters")
>   .head(2)
>   .sort("letters");
> >>
shape: (5, 2)
╭─────────┬─────╮
│ letters ┆ nrs │
│ ---     ┆ --- │
│ str     ┆ i64 │
╞═════════╪═════╡
│ "a"     ┆ 3   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "a"     ┆ 5   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "b"     ┆ 6   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "c"     ┆ 1   │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┤
│ "c"     ┆ 2   │
╰─────────┴─────╯
Copy

Aggregate the last values in the group.

Return the number of rows in each group.

Reduce the groups to the maximal value.

Reduce the groups to the mean values.

Return the median per group.

Reduce the groups to the minimal value.

Count the unique values per group.

Do a pivot operation based on the group key, a pivot column and an aggregation function on the values column.

Compute the quantile per group.

Reduce the groups to the sum.