polars.Series.scatter#

Series.scatter(
indices: Series | ndarray[Any, Any] | Sequence[int] | int,
values: int | float | str | bool | date | datetime | Sequence[int] | Sequence[float] | Sequence[bool] | Sequence[str] | Sequence[date] | Sequence[datetime] | Series | None,
) → Series[source]#

Set values at the index locations.

Parameters:
indices

Integers representing the index locations.

values

Replacement values.

Notes

Use of this function is frequently an anti-pattern, as it can block optimization (predicate pushdown, etc). Consider using pl.when(predicate).then(value).otherwise(self) instead.

Examples

>>> s = pl.Series("a", [1, 2, 3])
>>> s.scatter(1, 10)
shape: (3,)
Series: 'a' [i64]
[
        1
        10
        3
]

It is better to implement this as follows:

>>> s.to_frame().with_row_count("row_nr").select(
...     pl.when(pl.col("row_nr") == 1).then(10).otherwise(pl.col("a"))
... )
shape: (3, 1)
┌─────────┐
│ literal │
│ ---     │
│ i64     │
╞═════════╡
│ 1       │
│ 10      │
│ 3       │
└─────────┘