a     2
        b     3
        dtype: int64
        >>> ser.groupby(level=0).size()
        a    2
        b    1
        dtype: int64

        >>> data = [[1, 2, 3], [1, 5, 6], [7, 8, 9]]
        >>> df = pd.DataFrame(data, columns=["a", "b", "c"],
        ...                   index=["owl", "toucan", "eagle"])
        >>> df
                a  b  c
        owl     1  2  3
        toucan  1  5  6
        eagle   7  8  9
        >>> df.groupby("a").size()
        a
        1    2
        7    1
        dtype: int64

        For Resampler:

        >>> ser = pd.Series([1, 2, 3], index=pd.DatetimeIndex(
        ...                 ['2023-01-01', '2023-01-15', '2023-02-01']))
        >>> ser
        2023-01-01    1
        2023-01-15    2
        2023-02-01    3
        dtype: int64
        >>> ser.resample('MS').size()
        2023-01-01    2
        2023-02-01    1
        Freq: MS, dtype: int64
        NZnumpy_nullableZ