polars.Series.rolling_skew#

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

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

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)