polars.Series.rolling_skew

Series.rolling_skew(
    window_size: int,
    *,
    bias: bool = True,
    min_samples: int | None = None,
    center: bool = False,
) → Series

Compute a rolling skew.

Warning

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

The window at a given row includes the row itself and the window_size - 1 elements before it.

Parameters:

window_size

Integer size of the rolling window.

bias

If False, the calculations are corrected for statistical bias.

min_samples

The number of values in the window that should be non-null before computing a result. If set to None (default), it will be set equal to window_size.

center

Set the labels at the center of the window.

See also

Series.skew

Examples

>>> pl.Series([1, 4, 2, 9]).rolling_skew(3)
shape: (4,)
Series: '' [f64]
[
    null
    null
    0.381802
    0.47033
]

Note how the values match

>>> pl.Series([1, 4, 2]).skew(), pl.Series([4, 2, 9]).skew()
(0.38180177416060584, 0.47033046033698594)