polars.DataFrame.sort#
- DataFrame.sort(
- by: IntoExpr | Iterable[IntoExpr],
- *more_by: IntoExpr,
- descending: bool | Sequence[bool] = False,
- nulls_last: bool | Sequence[bool] = False,
- multithreaded: bool = True,
- maintain_order: bool = False,
Sort the dataframe by the given columns.
- Parameters:
- by
Column(s) to sort by. Accepts expression input, including selectors. Strings are parsed as column names.
- *more_by
Additional columns to sort by, specified as positional arguments.
- descending
Sort in descending order. When sorting by multiple columns, can be specified per column by passing a sequence of booleans.
- nulls_last
Place null values last; can specify a single boolean applying to all columns or a sequence of booleans for per-column control.
- multithreaded
Sort using multiple threads.
- maintain_order
Whether the order should be maintained if elements are equal.
Examples
Pass a single column name to sort by that column.
>>> df = pl.DataFrame( ... { ... "a": [1, 2, None], ... "b": [6.0, 5.0, 4.0], ... "c": ["a", "c", "b"], ... } ... ) >>> df.sort("a") shape: (3, 3) ┌──────┬─────┬─────┐ │ a ┆ b ┆ c │ │ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str │ ╞══════╪═════╪═════╡ │ null ┆ 4.0 ┆ b │ │ 1 ┆ 6.0 ┆ a │ │ 2 ┆ 5.0 ┆ c │ └──────┴─────┴─────┘
Sorting by expressions is also supported.
>>> df.sort(pl.col("a") + pl.col("b") * 2, nulls_last=True) shape: (3, 3) ┌──────┬─────┬─────┐ │ a ┆ b ┆ c │ │ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str │ ╞══════╪═════╪═════╡ │ 2 ┆ 5.0 ┆ c │ │ 1 ┆ 6.0 ┆ a │ │ null ┆ 4.0 ┆ b │ └──────┴─────┴─────┘
Sort by multiple columns by passing a list of columns.
>>> df.sort(["c", "a"], descending=True) shape: (3, 3) ┌──────┬─────┬─────┐ │ a ┆ b ┆ c │ │ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str │ ╞══════╪═════╪═════╡ │ 2 ┆ 5.0 ┆ c │ │ null ┆ 4.0 ┆ b │ │ 1 ┆ 6.0 ┆ a │ └──────┴─────┴─────┘
Or use positional arguments to sort by multiple columns in the same way.
>>> df.sort("c", "a", descending=[False, True]) shape: (3, 3) ┌──────┬─────┬─────┐ │ a ┆ b ┆ c │ │ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str │ ╞══════╪═════╪═════╡ │ 1 ┆ 6.0 ┆ a │ │ null ┆ 4.0 ┆ b │ │ 2 ┆ 5.0 ┆ c │ └──────┴─────┴─────┘