pandas.core.groupby.DataFrameGroupBy.groups#

property DataFrameGroupBy.groups[source]#

Dict {group name -> group labels}.

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}