polars.Expr.cum_sum#

Expr.cum_sum(*, reverse: bool = False) → Self[source]#

Get an array with the cumulative sum computed at every element.

Parameters:

reverse: Reverse the operation.

Notes

Dtypes in {Int8, UInt8, Int16, UInt16} are cast to Int64 before summing to prevent overflow issues.

Examples

>>> df = pl.DataFrame({"a": [1, 2, 3, 4]})
>>> df.with_columns(
...     pl.col("a").cum_sum().alias("cum_sum"),
...     pl.col("a").cum_sum(reverse=True).alias("cum_sum_reverse"),
... )
shape: (4, 3)
┌─────┬─────────┬─────────────────┐
│ a   ┆ cum_sum ┆ cum_sum_reverse │
│ --- ┆ ---     ┆ ---             │
│ i64 ┆ i64     ┆ i64             │
╞═════╪═════════╪═════════════════╡
│ 1   ┆ 1       ┆ 10              │
│ 2   ┆ 3       ┆ 9               │
│ 3   ┆ 6       ┆ 7               │
│ 4   ┆ 10      ┆ 4               │
└─────┴─────────┴─────────────────┘

Null values are excluded, but can also be filled by calling forward_fill.

>>> df = pl.DataFrame({"values": [None, 10, None, 8, 9, None, 16, None]})
>>> df.with_columns(
...     pl.col("values").cum_sum().alias("value_cum_sum"),
...     pl.col("values")
...     .cum_sum()
...     .forward_fill()
...     .alias("value_cum_sum_all_filled"),
... )
shape: (8, 3)
┌────────┬───────────────┬──────────────────────────┐
│ values ┆ value_cum_sum ┆ value_cum_sum_all_filled │
│ ---    ┆ ---           ┆ ---                      │
│ i64    ┆ i64           ┆ i64                      │
╞════════╪═══════════════╪══════════════════════════╡
│ null   ┆ null          ┆ null                     │
│ 10     ┆ 10            ┆ 10                       │
│ null   ┆ null          ┆ 10                       │
│ 8      ┆ 18            ┆ 18                       │
│ 9      ┆ 27            ┆ 27                       │
│ null   ┆ null          ┆ 27                       │
│ 16     ┆ 43            ┆ 43                       │
│ null   ┆ null          ┆ 43                       │
└────────┴───────────────┴──────────────────────────┘