polars.Expr.sort#

Expr.sort(*, descending: bool = False, nulls_last: bool = False) → Self[source]#

Sort this column.

When used in a projection/selection context, the whole column is sorted. When used in a groupby context, the groups are sorted.

Parameters:

descending: Sort in descending order.
nulls_last: Place null values last.

Examples

>>> df = pl.DataFrame(
...     {
...         "a": [1, None, 3, 2],
...     }
... )
>>> df.select(pl.col("a").sort())
shape: (4, 1)
┌──────┐
│ a    │
│ ---  │
│ i64  │
╞══════╡
│ null │
│ 1    │
│ 2    │
│ 3    │
└──────┘
>>> df.select(pl.col("a").sort(descending=True))
shape: (4, 1)
┌──────┐
│ a    │
│ ---  │
│ i64  │
╞══════╡
│ null │
│ 3    │
│ 2    │
│ 1    │
└──────┘
>>> df.select(pl.col("a").sort(nulls_last=True))
shape: (4, 1)
┌──────┐
│ a    │
│ ---  │
│ i64  │
╞══════╡
│ 1    │
│ 2    │
│ 3    │
│ null │
└──────┘

When sorting in a groupby context, the groups are sorted.

>>> df = pl.DataFrame(
...     {
...         "group": ["one", "one", "one", "two", "two", "two"],
...         "value": [1, 98, 2, 3, 99, 4],
...     }
... )
>>> df.groupby("group").agg(pl.col("value").sort())  
shape: (2, 2)
┌───────┬────────────┐
│ group ┆ value      │
│ ---   ┆ ---        │
│ str   ┆ list[i64]  │
╞═══════╪════════════╡
│ two   ┆ [3, 4, 99] │
│ one   ┆ [1, 2, 98] │
└───────┴────────────┘