
        Parameters
        ----------
        indices : array-like
            An array of ints indicating which positions to take in each group.
        axis : {0 or 'index', 1 or 'columns', None}, default 0
            The axis on which to select elements. ``0`` means that we are
            selecting rows, ``1`` means that we are selecting columns.
            For `SeriesGroupBy` this parameter is unused and defaults to 0.
        **kwargs
            For compatibility with :meth:`numpy.take`. Has no effect on the
            output.

        Returns
        -------
        Series
            A Series containing the elements taken from each group.

        See Also
        --------
        Series.take : Take elements from a Series along an axis.
        Series.loc : Select a subset of a DataFrame by labels.
        Series.iloc : Select a subset of a DataFrame by positions.
        numpy.take : Take elements from an array along an axis.
        SeriesGroupBy.nth : Similar to take, won't raise if indices don't exist.

        Examples
        --------
        >>> df = pd.DataFrame([('falcon', 'bird', 389.0),
        ...                    ('parrot', 'bird', 24.0),
        ...                    ('lion', 'mammal', 80.5),
        ...                    ('monkey', 'mammal', np.nan),
        ...                    ('rabbit', 'mammal', 15.0)],
        ...                   columns=['name', 'class', 'max_speed'],
        ...                   index=[4, 3, 2, 1, 0])
        >>> df
             name   class  max_speed
        4  falcon    bird      389.0
        3  parrot    bird       24.0
        2    lion  mammal       80.5
        1  monkey  mammal        NaN
        0  rabbit  mammal       15.0
        >>> gb = df["name"].groupby([1, 1, 2, 2, 2])

        Take elements at positions 0 and 1 along the axis 0 in each group (default).

        >>> gb.take([0, 1])
        1  4    falcon
           3    parrot
        2  2      lion
           1    monkey
        Name: name, dtype: object

        We may take elements using negative integers for positive indices,
        starting from the end of the object, just like with Python lists.

        >>> gb.take([-1, -2])
        1  3    parrot
           4    falcon
        2  0    rabbit
           1    monkey
        Name: name, dtype: object
        rc