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) Series[source]#

Compute a rolling quantile.

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
]