- Series.cumulative_eval(expr: Expr, min_periods: int = 1, parallel: bool = False) Series [source]#
Run an expression over a sliding window that increases 1 slot every iteration.
Expression to evaluate
Number of valid values there should be in the window before the expression is evaluated. valid values = length - null_count
Run in parallel. Don’t do this in a groupby or another operation that already has much parallelization.
This functionality is experimental and may change without it being considered a breaking change.
This can be really slow as it can have O(n^2) complexity. Don’t use this for operations that visit all elements.
>>> s = pl.Series("values", [1, 2, 3, 4, 5]) >>> s.cumulative_eval(pl.element().first() - pl.element().last() ** 2) shape: (5,) Series: 'values' [f64] [ 0.0 -3.0 -8.0 -15.0 -24.0 ]