BUG: fixes indexing with monotonic decreasing DTI (#19362) (#20677)

doc/source/whatsnew/v0.23.0.txt

@@ -1113,6 +1113,7 @@ Indexing
 - Bug in :meth:`DataFrame.first_valid_index` and :meth:`DataFrame.last_valid_index` in presence of entire rows of NaNs in the middle of values (:issue:`20499`).
 - Bug in :class:`IntervalIndex` where some indexing operations were not supported for overlapping or non-monotonic ``uint64`` data (:issue:`20636`)
 - Bug in ``Series.is_unique`` where extraneous output in stderr is shown if Series contains objects with ``__ne__`` defined (:issue:`20661`)
+- Bug in partial string indexing on a ``Series/DataFrame`` with a monotonic decreasing ``DatetimeIndex`` (:issue:`19362`)
 
 MultiIndex
 ^^^^^^^^^^

pandas/core/indexes/datetimelike.py

@@ -342,7 +342,8 @@ def _format_with_header(self, header, **kwargs):
     def __contains__(self, key):
         try:
             res = self.get_loc(key)
-            return is_scalar(res) or type(res) == slice or np.any(res)
+            return (is_scalar(res) or isinstance(res, slice) or
+                    (is_list_like(res) and len(res)))
         except (KeyError, TypeError, ValueError):
             return False
 

pandas/tests/indexes/datetimes/test_partial_slicing.py

@@ -91,6 +91,27 @@ def test_slice_duplicate_monotonic(self):
         expected = Timestamp('2017-01-01')
         assert result == expected
 
+    def test_monotone_DTI_indexing_bug(self):
+        # GH 19362
+        # Testing accessing the first element in a montononic descending
+        # partial string indexing.
+
+        df = pd.DataFrame(list(range(5)))
+        date_list = ['2018-01-02', '2017-02-10', '2016-03-10',
+                     '2015-03-15', '2014-03-16']
+        date_index = pd.to_datetime(date_list)
+        df['date'] = date_index
+        expected = pd.DataFrame({0: list(range(5)), 'date': date_index})
+        tm.assert_frame_equal(df, expected)
+
+        df = pd.DataFrame({'A': [1, 2, 3]},
+                          index=pd.date_range('20170101',
+                                              periods=3)[::-1])
+        expected = pd.DataFrame({'A': 1},
+                                index=pd.date_range('20170103',
+                                                    periods=1))
+        tm.assert_frame_equal(df.loc['2017-01-03'], expected)
+
     def test_slice_year(self):
         dti = DatetimeIndex(freq='B', start=datetime(2005, 1, 1), periods=500)