Cumulative min 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', 'a', 'b', 'b', 'b']
>>> ser = pd.Series([1, 6, 2, 3, 0, 4], index=lst)
>>> ser
a 1
a 6
a 2
b 3
b 0
b 4
dtype: int64
>>> ser.groupby(level=0).cummin()
a 1
a 1
a 1
b 3
b 0
b 0
dtype: int64
For DataFrameGroupBy:
>>> data = [[1, 0, 2], [1, 1, 5], [6, 6, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
... index=["snake", "rabbit", "turtle"])
>>> df
a b c
snake 1 0 2
rabbit 1 1 5
turtle 6 6 9
>>> df.groupby("a").groups
{1: ['snake', 'rabbit'], 6: ['turtle']}
>>> df.groupby("a").cummin()
b c
snake 0 2
rabbit 0 2
turtle 6 9
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https://pandas.pydata.org/pandas-docs/version/2.3.0/reference/api/pandas.core.groupby.SeriesGroupBy.cummin.html