polars.dataframe.group_by.GroupBy.first#

GroupBy.first(*, ignore_nulls: bool = False) → DataFrame[source]#

Aggregate the first values in the group.

Parameters:

ignore_nulls: Ignore null values (default False). If set to True, the first non-null value for each aggregation is returned, otherwise None is returned if no non-null value exists.

Examples

>>> df = pl.DataFrame(
...     {
...         "a": [1, 2, 2, 3, 4, 5],
...         "b": [0.5, 0.5, 4, 10, 13, 14],
...         "c": [None, True, True, False, False, True],
...         "d": ["Apple", "Orange", "Apple", "Apple", "Banana", "Banana"],
...     }
... )
>>> df.group_by("d", maintain_order=True).first()
shape: (3, 4)
┌────────┬─────┬──────┬───────┐
│ d      ┆ a   ┆ b    ┆ c     │
│ ---    ┆ --- ┆ ---  ┆ ---   │
│ str    ┆ i64 ┆ f64  ┆ bool  │
╞════════╪═════╪══════╪═══════╡
│ Apple  ┆ 1   ┆ 0.5  ┆ null  │
│ Orange ┆ 2   ┆ 0.5  ┆ true  │
│ Banana ┆ 4   ┆ 13.0 ┆ false │
└────────┴─────┴──────┴───────┘
>>> df.group_by("d", maintain_order=True).first(ignore_nulls=True)
shape: (3, 4)
┌────────┬─────┬──────┬───────┐
│ d      ┆ a   ┆ b    ┆ c     │
│ ---    ┆ --- ┆ ---  ┆ ---   │
│ str    ┆ i64 ┆ f64  ┆ bool  │
╞════════╪═════╪══════╪═══════╡
│ Apple  ┆ 1   ┆ 0.5  ┆ true  │
│ Orange ┆ 2   ┆ 0.5  ┆ true  │
│ Banana ┆ 4   ┆ 13.0 ┆ false │
└────────┴─────┴──────┴───────┘