BUG: Fix Series.sort_values descending & mergesort

The solution uses the `nargsort` function, which was created to handle
in one place the intricacies of sorting. Not adapting Series.sort_values
to use may have been an oversight.

closes #28697

Author: has2k1

doc/source/whatsnew/v1.0.0.rst

@@ -445,6 +445,8 @@ Other
 - Fix corrupted error message when calling ``pandas.libs._json.encode()`` on a 0d array (:issue:`18878`)
 - Fix :class:`AbstractHolidayCalendar` to return correct results for
   years after 2030 (now goes up to 2200) (:issue:`27790`)
+- Bug in :meth:`Series.sort_values` when ``ascending`` is set to ``False`` and
+  ``kind`` is set to ``mergesort`` (:issue:`28697`)
 
 
 .. _whatsnew_1000.contributors:

pandas/core/series.py

@@ -75,6 +75,7 @@
 from pandas.core.indexes.timedeltas import TimedeltaIndex
 from pandas.core.indexing import check_bool_indexer
 from pandas.core.internals import SingleBlockManager
+from pandas.core.sorting import nargsort
 from pandas.core.strings import StringMethods
 from pandas.core.tools.datetimes import to_datetime
 
@@ -3077,26 +3078,6 @@ def sort_values(
                 "sort in-place you must create a copy"
             )
 
-        def _try_kind_sort(arr):
-            # easier to ask forgiveness than permission
-            try:
-                # if kind==mergesort, it can fail for object dtype
-                return arr.argsort(kind=kind)
-            except TypeError:
-                # stable sort not available for object dtype
-                # uses the argsort default quicksort
-                return arr.argsort(kind="quicksort")
-
-        arr = self._values
-        sortedIdx = np.empty(len(self), dtype=np.int32)
-
-        bad = isna(arr)
-
-        good = ~bad
-        idx = ibase.default_index(len(self))
-
-        argsorted = _try_kind_sort(arr[good])
-
         if is_list_like(ascending):
             if len(ascending) != 1:
                 raise ValueError(
@@ -3108,21 +3089,10 @@ def _try_kind_sort(arr):
         if not is_bool(ascending):
             raise ValueError("ascending must be boolean")
 
-        if not ascending:
-            argsorted = argsorted[::-1]
-
-        if na_position == "last":
-            n = good.sum()
-            sortedIdx[:n] = idx[good][argsorted]
-            sortedIdx[n:] = idx[bad]
-        elif na_position == "first":
-            n = bad.sum()
-            sortedIdx[n:] = idx[good][argsorted]
-            sortedIdx[:n] = idx[bad]
-        else:
-            raise ValueError("invalid na_position: {!r}".format(na_position))
+        arr = self._values
+        indexer = nargsort(arr, kind=kind, ascending=ascending, na_position=na_position)
 
-        result = self._constructor(arr[sortedIdx], index=self.index[sortedIdx])
+        result = self._constructor(arr[indexer], index=self.index[indexer])
 
         if inplace:
             self._update_inplace(result)

pandas/tests/series/test_sorting.py

@@ -86,6 +86,17 @@ def test_sort_values(self, datetime_series):
         with pytest.raises(ValueError, match=msg):
             s.sort_values(inplace=True)
 
+    def test_sort_values_mergesort(self):
+        ser = Series([1, 2, 1, 3], ["first", "b", "second", "c"])
+        expected = Series([1, 1, 2, 3], ["first", "second", "b", "c"])
+        result = ser.sort_values(kind="mergesort")
+        tm.assert_series_equal(expected, result)
+
+        # ascending=False is not just a reverse of ascending=True
+        expected = Series([3, 2, 1, 1], ["c", "b", "first", "second"])
+        result = ser.sort_values(ascending=False, kind="mergesort")
+        tm.assert_series_equal(expected, result)
+
     def test_sort_index(self, datetime_series):
         rindex = list(datetime_series.index)
         random.shuffle(rindex)