polars.Expr.arr.sort#

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

Sort the arrays in this column.

Parameters:

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

Examples

>>> df = pl.DataFrame(
...     {
...         "a": [[3, 2, 1], [9, 1, 2]],
...     },
...     schema={"a": pl.Array(pl.Int64, 3)},
... )
>>> df.with_columns(sort=pl.col("a").arr.sort())
shape: (2, 2)
┌───────────────┬───────────────┐
│ a             ┆ sort          │
│ ---           ┆ ---           │
│ array[i64, 3] ┆ array[i64, 3] │
╞═══════════════╪═══════════════╡
│ [3, 2, 1]     ┆ [1, 2, 3]     │
│ [9, 1, 2]     ┆ [1, 2, 9]     │
└───────────────┴───────────────┘
>>> df.with_columns(sort=pl.col("a").arr.sort(descending=True))
shape: (2, 2)
┌───────────────┬───────────────┐
│ a             ┆ sort          │
│ ---           ┆ ---           │
│ array[i64, 3] ┆ array[i64, 3] │
╞═══════════════╪═══════════════╡
│ [3, 2, 1]     ┆ [3, 2, 1]     │
│ [9, 1, 2]     ┆ [9, 2, 1]     │
└───────────────┴───────────────┘