DataFrame.sort_index() with ascending passed as a list on a single level index gives wrong result

[aniaan]

I found some problems while using data_frame sort_index, first, create dataframe

data = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), columns=['a', 'b', 'c'])
data = data.set_index('a')
data.sort_index(level=['a'], ascending=[False])

Then I want to sort index "a" in descending order,

data.sort_index(level=['a'], ascending=[False])

The above code does not sort index a in descending order, I found the reason is that this dataframe is a single index structure, so when ascending = list is passed, it does not take effect

pandas/pandas/core/frame.py

Lines 4777 to 4783 in bf613c1

	if level is not None:
	new_axis, indexer = labels.sortlevel(
	level, ascending=ascending, sort_remaining=sort_remaining
	)
	elif isinstance(labels, ABCMultiIndex):

Because when it is used, the index may be single index or multi-index. In order to use the effect uniformly,I think there should be a judgment here. If index is a single index and ascending type == list, ascending should be equal to ascending [0]，This may be more user friendly

If yes, can I mention pr

[Dr-Irv]

It seems that this works fine:

 data.sort_index(level=['a'], ascending=False)

But the following does not

data.sort_index(level=['a'], ascending=[False])

PR welcome

[Dr-Irv]

Possible fix is to do 2 things:

1. In indexes/base.py in sortlevel() add a check on the type of ascending, and if a list and length 1, convert to a True/False value.
2. If a list and length greater than 1, raise an Exception

[heyitskevin]

take

[aniaan]

take