def argsort(self, *args, **kwargs):<EOL>
<EOL>return super().argsort(*args, **kwargs)<EOL>
Return the indices that would sort the Categorical.

Parameters
----------
ascending : bool, default True
    Whether the indices should result in an ascending
    or descending sort.
kind : {'quicksort', 'mergesort', 'heapsort'}, optional
    Sorting algorithm.
*args, **kwargs:
    passed through to :func:`numpy.argsort`.

Returns
-------
numpy.array

See Also
--------
numpy.ndarray.argsort

Notes
-----
While an ordering is applied to the category values, arg-sorting
in this context refers more to organizing and grouping together
based on matching category values. Thus, this function can be
called on an unordered Categorical instance unlike the functions
'Categorical.min' and 'Categorical.max'.

Examples
--------
>>> pd.Categorical(['b', 'b', 'a', 'c']).argsort()
array([2, 0, 1, 3])

>>> cat = pd.Categorical(['b', 'b', 'a', 'c'],
...                      categories=['c', 'b', 'a'],
...                      ordered=True)
>>> cat.argsort()
array([3, 0, 1, 2])