pandas.MultiIndex.sortlevel

MultiIndex.sortlevel(level=0, ascending=True, sort_remaining=True, na_position='first')[source]

Sort MultiIndex at the requested level.

The result will respect the original ordering of the associated factor at that level.

Parameters:

level:list-like, int or str, default 0

If a string is given, must be a name of the level. If list-like must be names or ints of levels.

ascending:bool, default True

False to sort in descending order. Can also be a list to specify a directed ordering.

sort_remaining:sort by the remaining levels after level

na_position:{‘first’ or ‘last’}, default ‘first’

Argument ‘first’ puts NaNs at the beginning, ‘last’ puts NaNs at the end.

Added in version 2.1.0.

Returns:

sorted_index:pd.MultiIndex

Resulting index.

indexer:np.ndarray[np.intp]

Indices of output values in original index.

Examples

>>> mi = pd.MultiIndex.from_arrays([[0, 0], [2, 1]])
>>> mi
MultiIndex([(0, 2),
            (0, 1)],
           )

>>> mi.sortlevel()
(MultiIndex([(0, 1),
            (0, 2)],
           ), array([1, 0]))

>>> mi.sortlevel(sort_remaining=False)
(MultiIndex([(0, 2),
            (0, 1)],
           ), array([0, 1]))

>>> mi.sortlevel(1)
(MultiIndex([(0, 1),
            (0, 2)],
           ), array([1, 0]))

>>> mi.sortlevel(1, ascending=False)
(MultiIndex([(0, 2),
            (0, 1)],
           ), array([0, 1]))