polars.cumreduce#

polars.cumreduce( function: Callable[[Series, Series], Series], exprs: Sequence[Expr | str] | Expr, ) → Expr[source]#

Cumulatively accumulate over multiple columns horizontally/ row wise with a left fold.

Every cumulative result is added as a separate field in a Struct column.

Parameters:

function: Function to apply over the accumulator and the value. Fn(acc, value) -> new_value
exprs: Expressions to aggregate over. May also be a wildcard expression.

Examples

>>> df = pl.DataFrame(
...     {
...         "a": [1, 2, 3],
...         "b": [3, 4, 5],
...         "c": [5, 6, 7],
...     }
... )
>>> df
shape: (3, 3)
┌─────┬─────┬─────┐
│ a   ┆ b   ┆ c   │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ i64 │
╞═════╪═════╪═════╡
│ 1   ┆ 3   ┆ 5   │
│ 2   ┆ 4   ┆ 6   │
│ 3   ┆ 5   ┆ 7   │
└─────┴─────┴─────┘

>>> df.select(
...     pl.cumreduce(function=lambda acc, x: acc + x, exprs=pl.col("*")).alias(
...         "cumreduce"
...     ),
... )
shape: (3, 1)
┌───────────┐
│ cumreduce │
│ ---       │
│ struct[3] │
╞═══════════╡
│ {1,4,9}   │
│ {2,6,12}  │
│ {3,8,15}  │
└───────────┘