polars.Expr.rolling_kurtosis#

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

Compute a rolling kurtosis.

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.
fisherbool, optional: If True, Fisher’s definition is used (normal ==> 0.0). If False, Pearson’s definition is used (normal ==> 3.0).
biasbool, optional: 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

Expr.kurtosis

Examples

>>> df = pl.DataFrame({"a": [1, 4, 2, 9]})
>>> df.select(pl.col("a").rolling_kurtosis(3))
shape: (4, 1)
┌──────┐
│ a    │
│ ---  │
│ f64  │
╞══════╡
│ null │
│ null │
│ -1.5 │
│ -1.5 │
└──────┘