polars.row_index#

polars.row_index(name: str = 'index') → Expr[source]#

Generates a sequence of integers.

The length of the returned sequence will match the context length, and the datatype will match the one returned by get_index_dtype().

Warning

This functionality is considered unstable. It may be changed at any point without it being considered a breaking change.

If you would like to generate sequences with custom offsets / length / step size / datatypes, it is recommended to use int_range instead.

Parameters:

name: Name of the returned column.

Returns:

Expr: Column of integers.

See also

int_range: Generate a range of integers.

Examples

>>> df = pl.DataFrame({"x": ["A", "A", "B", "B", "B"]})
>>> df.with_columns(pl.row_index(), pl.row_index("another_index"))
shape: (5, 3)
┌─────┬───────┬───────────────┐
│ x   ┆ index ┆ another_index │
│ --- ┆ ---   ┆ ---           │
│ str ┆ u32   ┆ u32           │
╞═════╪═══════╪═══════════════╡
│ A   ┆ 0     ┆ 0             │
│ A   ┆ 1     ┆ 1             │
│ B   ┆ 2     ┆ 2             │
│ B   ┆ 3     ┆ 3             │
│ B   ┆ 4     ┆ 4             │
└─────┴───────┴───────────────┘
>>> df.group_by("x").agg(pl.row_index()).sort("x")
shape: (2, 2)
┌─────┬───────────┐
│ x   ┆ index     │
│ --- ┆ ---       │
│ str ┆ list[u32] │
╞═════╪═══════════╡
│ A   ┆ [0, 1]    │
│ B   ┆ [0, 1, 2] │
└─────┴───────────┘
>>> df.select(pl.row_index())
shape: (5, 1)
┌───────┐
│ index │
│ ---   │
│ u32   │
╞═══════╡
│ 0     │
│ 1     │
│ 2     │
│ 3     │
│ 4     │
└───────┘