pandas.core.groupby.SeriesGroupBy.groups — pandas 3.0.0.dev0+2103.g41968a550a documentation (original) (raw)

property SeriesGroupBy.groups[source]#

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'): np.int64(2), Timestamp('2023-02-01 00:00:00'): np.int64(4)}