bigframes.pandas.api.typing.DataFrameGroupBy.cumsum

DataFrameGroupBy.cumsum(*args, numeric_only: bool = False, **kwargs) → DataFrame

Cumulative sum for each group.

Examples:

For SeriesGroupBy:

>>> lst = ['a', 'a', 'b']
>>> ser = bpd.Series([6, 2, 0], index=lst)
>>> ser.groupby(level=0).cumsum()
a    6
a    8
b    0
dtype: Int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [2, 6, 9]]
>>> df = bpd.DataFrame(data, columns=["a", "b", "c"],
...                   index=["fox", "gorilla", "lion"])
>>> df.groupby("a").cumsum()
          b  c
fox       8  2
gorilla  10  7
lion      6  9

[3 rows x 2 columns]

Returns:

Cumulative sum for each group.

Return type:

bigframes.pandas.DataFrame or bigframes.pandas.Series