polars.int_ranges

polars.int_ranges(
    start: int | IntoExprColumn = 0,
    end: int | IntoExprColumn | None = None,
    step: int | IntoExprColumn = 1,
    *,
    dtype: PolarsIntegerType | DataTypeExpr = Int64,
    eager: bool = False,
) → Expr | Series

Generate a range of integers for each row of the input columns.

Parameters:

start

Start of the range (inclusive). Defaults to 0.

end

End of the range (exclusive). If set to None (default), the value of start is used and start is set to 0.

step

Step size of the range.

dtype

Integer data type of the ranges. Defaults to Int64.

eager

Evaluate immediately and return a Series. If set to False (default), return an expression instead.

Returns:

Expr or Series

Column of data type List(dtype).

See also

int_range

Generate a single range of integers.

Examples

>>> df = pl.DataFrame({"start": [1, -1], "end": [3, 2]})
>>> df.with_columns(int_range=pl.int_ranges("start", "end"))
shape: (2, 3)
┌───────┬─────┬────────────┐
│ start ┆ end ┆ int_range  │
│ ---   ┆ --- ┆ ---        │
│ i64   ┆ i64 ┆ list[i64]  │
╞═══════╪═════╪════════════╡
│ 1     ┆ 3   ┆ [1, 2]     │
│ -1    ┆ 2   ┆ [-1, 0, 1] │
└───────┴─────┴────────────┘

end can be omitted for a shorter syntax.

>>> df.select("end", int_range=pl.int_ranges("end"))
shape: (2, 2)
┌─────┬───────────┐
│ end ┆ int_range │
│ --- ┆ ---       │
│ i64 ┆ list[i64] │
╞═════╪═══════════╡
│ 3   ┆ [0, 1, 2] │
│ 2   ┆ [0, 1]    │
└─────┴───────────┘