polars.dataframe.group_by.GroupBy.last#

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

Aggregate the last values in the group.

Parameters:

ignore_nulls: Ignore null values (default False). If set to True, the last non-null value for each column 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, 14, None],
...         "c": [True, True, True, None, False, True],
...         "d": ["Apple", "Orange", "Apple", "Apple", "Banana", "Banana"],
...     }
... )
>>> df.group_by("d", maintain_order=True).last()
shape: (3, 4)
┌────────┬─────┬──────┬──────┐
│ d      ┆ a   ┆ b    ┆ c    │
│ ---    ┆ --- ┆ ---  ┆ ---  │
│ str    ┆ i64 ┆ f64  ┆ bool │
╞════════╪═════╪══════╪══════╡
│ Apple  ┆ 3   ┆ 10.0 ┆ null │
│ Orange ┆ 2   ┆ 0.5  ┆ true │
│ Banana ┆ 5   ┆ null ┆ true │
└────────┴─────┴──────┴──────┘
>>> df.group_by("d", maintain_order=True).last(ignore_nulls=True)
shape: (3, 4)
┌────────┬─────┬──────┬──────┐
│ d      ┆ a   ┆ b    ┆ c    │
│ ---    ┆ --- ┆ ---  ┆ ---  │
│ str    ┆ i64 ┆ f64  ┆ bool │
╞════════╪═════╪══════╪══════╡
│ Apple  ┆ 3   ┆ 10.0 ┆ true │
│ Orange ┆ 2   ┆ 0.5  ┆ true │
│ Banana ┆ 5   ┆ 14.0 ┆ true │
└────────┴─────┴──────┴──────┘