pandas.core.groupby.DataFrameGroupBy.groups

property DataFrameGroupBy.groups

Dict {group name -> group labels}.

This property provides a dictionary representation of the groupings formed during a groupby operation, where each key represents a unique group value from the specified column(s), and each value is a list of index labels that belong to that group.

See also

core.groupby.DataFrameGroupBy.get_group

Retrieve group from a DataFrameGroupBy object with provided name.

core.groupby.SeriesGroupBy.get_group

Retrieve group from a SeriesGroupBy object with provided name.

core.resample.Resampler.get_group

Retrieve group from a Resampler object with provided name.

Examples

For SeriesGroupBy:

>>> lst = ["a", "a", "b"]
>>> ser = pd.Series([1, 2, 3], index=lst)
>>> ser
a    1
a    2
b    3
dtype: int64
>>> ser.groupby(level=0).groups
{'a': ['a', 'a'], 'b': ['b']}

For DataFrameGroupBy:

>>> data = [[1, 2, 3], [1, 5, 6], [7, 8, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"])
>>> df
   a  b  c
0  1  2  3
1  1  5  6
2  7  8  9
>>> df.groupby(by="a").groups
{1: [0, 1], 7: [2]}

For Resampler:

>>> ser = pd.Series(
...     [1, 2, 3, 4],
...     index=pd.DatetimeIndex(
...         ["2023-01-01", "2023-01-15", "2023-02-01", "2023-02-15"]
...     ),
... )
>>> ser
2023-01-01    1
2023-01-15    2
2023-02-01    3
2023-02-15    4
dtype: int64
>>> ser.resample("MS").groups
{Timestamp('2023-01-01 00:00:00'): 2, Timestamp('2023-02-01 00:00:00'): 4}