Cumulative sum for each group.
See also
Series.groupbyApply a function groupby to a Series.
DataFrame.groupbyApply a function groupby to each row or column of a DataFrame.
Examples
For SeriesGroupBy:
>>> lst = ['a', 'a', 'b']
>>> ser = pd.Series([6, 2, 0], index=lst)
>>> ser
a 6
a 2
b 0
dtype: int64
>>> 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 = pd.DataFrame(data, columns=["a", "b", "c"],
... index=["fox", "gorilla", "lion"])
>>> df
a b c
fox 1 8 2
gorilla 1 2 5
lion 2 6 9
>>> df.groupby("a").groups
{1: ['fox', 'gorilla'], 2: ['lion']}
>>> df.groupby("a").cumsum()
b c
fox 8 2
gorilla 10 7
lion 6 9
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/2.3.0/reference/api/pandas.core.groupby.SeriesGroupBy.cumsum.html