polars.Expr.rolling_skew#
- Expr.rolling_skew(window_size: int, *, bias: bool = True) Expr [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 will include 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.
Examples
>>> df = pl.DataFrame({"a": [1, 4, 2, 9]}) >>> df.select(pl.col("a").rolling_skew(3)) shape: (4, 1) ┌──────────┐ │ a │ │ --- │ │ f64 │ ╞══════════╡ │ null │ │ null │ │ 0.381802 │ │ 0.47033 │ └──────────┘
Note how the values match the following:
>>> pl.Series([1, 4, 2]).skew(), pl.Series([4, 2, 9]).skew() (0.38180177416060584, 0.47033046033698594)