polars.Series.rolling_quantile#
- Series.rolling_quantile(
- quantile: float,
- interpolation: RollingInterpolationMethod = 'nearest',
- window_size: int = 2,
- weights: list[float] | None = None,
- min_periods: int | None = None,
- *,
- center: bool = False,
Compute a rolling quantile.
The window at a given row will include the row itself and the window_size - 1 elements before it.
- Parameters:
- quantile
Quantile between 0.0 and 1.0.
- interpolation{‘nearest’, ‘higher’, ‘lower’, ‘midpoint’, ‘linear’}
Interpolation method.
- window_size
The length of the window.
- weights
An optional slice with the same length as the window that will be multiplied elementwise with the values in the window.
- min_periods
The number of values in the window that should be non-null before computing a result. If None, it will be set equal to window size.
- center
Set the labels at the center of the window
Examples
>>> s = pl.Series("a", [1.0, 2.0, 3.0, 4.0, 6.0, 8.0]) >>> s.rolling_quantile(quantile=0.33, window_size=3) shape: (6,) Series: 'a' [f64] [ null null 1.0 2.0 3.0 4.0 ] >>> s.rolling_quantile(quantile=0.33, interpolation="linear", window_size=3) shape: (6,) Series: 'a' [f64] [ null null 1.66 2.66 3.66 5.32 ]