Changes requested by @jreback

Author: Jean-Mathieu Deschenes

doc/source/whatsnew/v0.21.0.txt

@@ -144,7 +144,6 @@ Bug Fixes
 ~~~~~~~~~
 
 - Fixes regression in 0.20, :func:`Series.aggregate` and :func:`DataFrame.aggregate` allow dictionaries as return values again (:issue:`16741`)
-- Fixes regression when sorting by multiple columns on a datetime array with NaT values (:issue:`16836`)
 
 Conversion
 ^^^^^^^^^^
@@ -184,6 +183,7 @@ Sparse
 Reshaping
 ^^^^^^^^^
 
+- Fixes regression when sorting by multiple columns on a ``datetime64`` dtype ``Series`` with ``NaT`` values (:issue:`16836`)
 
 
 Numeric

pandas/tests/frame/test_sorting.py

@@ -89,22 +89,6 @@ def test_sort_values(self):
         with tm.assert_raises_regex(ValueError, msg):
             frame.sort_values(by=['A', 'B'], axis=0, ascending=[True] * 5)
 
-        # GH 16836
-
-        d1 = [Timestamp(x) for x in ['2016-01-01', '2015-01-01',
-                                     np.nan, '2016-01-01']]
-        d2 = [Timestamp(x) for x in ['2017-01-01', '2014-01-01',
-                                     '2016-01-01', '2015-01-01']]
-        df = pd.DataFrame({'a': d1, 'b': d2}, index=[0, 1, 2, 3])
-
-        d3 = [Timestamp(x) for x in ['2015-01-01', '2016-01-01',
-                                     '2016-01-01', np.nan]]
-        d4 = [Timestamp(x) for x in ['2014-01-01', '2015-01-01',
-                                     '2017-01-01', '2016-01-01']]
-        expected = pd.DataFrame({'a': d3, 'b': d4}, index=[1, 3, 0, 2])
-        sorted_df = df.sort_values(by=['a', 'b'], )
-        tm.assert_frame_equal(sorted_df, expected)
-
     def test_sort_values_inplace(self):
         frame = DataFrame(np.random.randn(4, 4), index=[1, 2, 3, 4],
                           columns=['A', 'B', 'C', 'D'])
@@ -348,6 +332,22 @@ def test_sort_nat_values_in_int_column(self):
         df_sorted = df.sort_values(["datetime", "float"], ascending=False)
         assert_frame_equal(df_sorted, df)
 
+        # GH 16836
+
+        d1 = [Timestamp(x) for x in ['2016-01-01', '2015-01-01',
+                                     np.nan, '2016-01-01']]
+        d2 = [Timestamp(x) for x in ['2017-01-01', '2014-01-01',
+                                     '2016-01-01', '2015-01-01']]
+        df = pd.DataFrame({'a': d1, 'b': d2}, index=[0, 1, 2, 3])
+
+        d3 = [Timestamp(x) for x in ['2015-01-01', '2016-01-01',
+                                     '2016-01-01', np.nan]]
+        d4 = [Timestamp(x) for x in ['2014-01-01', '2015-01-01',
+                                     '2017-01-01', '2016-01-01']]
+        expected = pd.DataFrame({'a': d3, 'b': d4}, index=[1, 3, 0, 2])
+        sorted_df = df.sort_values(by=['a', 'b'], )
+        tm.assert_frame_equal(sorted_df, expected)
+
 
 class TestDataFrameSortIndexKinds(TestData):