BUG: Index.sort_values with key

[jbrockmendel]

Index.sort_values does

idx = ensure_key_mapped(self, key)
_as = nargsort(
    items=idx, ascending=ascending, na_position=na_position, key=key
)

But when key is not None, nargsort does the ensure_key_mapped call again. And ensure_key_mapped is not idempotent.

If I remove the key=key from the nargsort call here, the only test that fails is TestRangeIndex::test_sort_values_key

sort_order = {8: 2, 6: 0, 4: 8, 2: 10, 0: 12}
values = RangeIndex(0, 10, 2)
result = values.sort_values(key=lambda x: x.map(sort_order))
expected = Index([4, 8, 6, 0, 2], dtype="int64")
tm.assert_index_equal(result, expected, check_exact=True)

but it isn't obvious to me expected here is correct. If we do pd.Series(values).sort_values(key=lambda x: x.map(sort_order)) we get a different ordering.

[rhshadrach]

expect here is indeed wrong; it's what you get when you apply the map twice allowing for nans when there are missing keys, with the nans placed at the end.

[jbrockmendel]

theres one other place in frame.py where we call nargsort with a key, good chance the same problem happens there too

[oscar-garzon]

is this issue still open?

[jbrockmendel]

@rhshadrach can you confirm that expected should be Index([6, 8, 4, 2, 0])?

[rhshadrach]

@rhshadrach can you confirm that expected should be Index([6, 8, 4, 2, 0])?

Yes - that's what I get.