int64
        b
        b    3
        dtype: int64

        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
        >>> for x, y in df.groupby(by=["a"]):
        ...     print(f'{x}\n{y}\n')
        (1,)
           a  b  c
        0  1  2  3
        1  1  5  6
        (7,)
           a  b  c
        2  7  8  9

        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
        >>> for x, y in ser.resample('MS'):
        ...     print(f'{x}\n{y}\n')
        2023-01-01 00:00:00
        2023-01-01    1
        2023-01-15    2
        dtype: int64
        2023-02-01 00:00:00
        2023-02-01    3
        2023-02-15    4
        dtype: int64
        rÊ