BUG: DatetimeIndex slicing with boolean Index raises TypeError

Author: sinhrks

doc/source/whatsnew/v0.24.0.txt

@@ -738,6 +738,7 @@ Indexing
 - Bug in :meth:`DataFrame.loc` when indexing with an :class:`IntervalIndex` (:issue:`19977`)
 - :class:`Index` no longer mangles ``None``, ``NaN`` and ``NaT``, i.e. they are treated as three different keys. However, for numeric Index all three are still coerced to a ``NaN`` (:issue:`22332`)
 - Bug in `scalar in Index` if scalar is a float while the ``Index`` is of integer dtype (:issue:`22085`)
+- Bug in :class:`Index` slicing with boolean :class:`Index` may raise ``TypeError`` (:issue:`22533`)
 
 Missing
 ^^^^^^^

pandas/core/arrays/datetimelike.py

@@ -171,7 +171,7 @@ def __getitem__(self, key):
             return self._box_func(val)
 
         if com.is_bool_indexer(key):
-            key = np.asarray(key)
+            key = np.asarray(key, dtype=bool)
             if key.all():
                 key = slice(0, None, None)
             else:

pandas/core/indexes/base.py

@@ -2070,7 +2070,7 @@ def __getitem__(self, key):
             return promote(getitem(key))
 
         if com.is_bool_indexer(key):
-            key = np.asarray(key)
+            key = np.asarray(key, dtype=bool)
 
         key = com.values_from_object(key)
         result = getitem(key)

pandas/core/indexes/multi.py

@@ -1607,7 +1607,7 @@ def __getitem__(self, key):
             return tuple(retval)
         else:
             if com.is_bool_indexer(key):
-                key = np.asarray(key)
+                key = np.asarray(key, dtype=bool)
                 sortorder = self.sortorder
             else:
                 # cannot be sure whether the result will be sorted

pandas/tests/indexes/datetimes/test_indexing.py

@@ -600,3 +600,25 @@ def test_get_loc_nat(self):
         # GH#20464
         index = DatetimeIndex(['1/3/2000', 'NaT'])
         assert index.get_loc(pd.NaT) == 1
+
+    @pytest.mark.parametrize('ind1', [[True] * 5, pd.Index([True] * 5)])
+    @pytest.mark.parametrize('ind2', [[True, False, True, False, False],
+                                      pd.Index([True, False, True, False,
+                                                False])])
+    def test_getitem_bool_index_all(self, ind1, ind2):
+        # GH#22533
+        idx = pd.date_range('2011-01-01', '2011-01-05', freq='D', name='idx')
+        tm.assert_index_equal(idx[ind1], idx)
+
+        expected = pd.DatetimeIndex(['2011-01-01', '2011-01-03'], name='idx')
+        tm.assert_index_equal(idx[ind2], expected)
+
+    @pytest.mark.parametrize('ind1', [[True], pd.Index([True])])
+    @pytest.mark.parametrize('ind2', [[False], pd.Index([False])])
+    def test_getitem_bool_index_single(self, ind1, ind2):
+        # GH#22533
+        idx = pd.DatetimeIndex(['2011-01-01'], name='idx')
+        tm.assert_index_equal(idx[ind1], idx)
+
+        expected = pd.DatetimeIndex([], name='idx')
+        tm.assert_index_equal(idx[ind2], expected)

pandas/tests/indexes/multi/test_indexing.py

@@ -224,6 +224,33 @@ def test_get_indexer_consistency(idx):
     assert indexer.dtype == np.intp
 
 
+@pytest.mark.parametrize('ind1', [[True] * 5, pd.Index([True] * 5)])
+@pytest.mark.parametrize('ind2', [[True, False, True, False, False],
+                                  pd.Index([True, False, True, False,
+                                            False])])
+def test_getitem_bool_index_all(ind1, ind2):
+    # GH#22533
+    idx = MultiIndex.from_tuples([(10, 1), (20, 2), (30, 3),
+                                  (40, 4), (50, 5)])
+    tm.assert_index_equal(idx[ind1], idx)
+
+    expected = MultiIndex.from_tuples([(10, 1), (30, 3)])
+    tm.assert_index_equal(idx[ind2], expected)
+
+
+@pytest.mark.parametrize('ind1', [[True], pd.Index([True])])
+@pytest.mark.parametrize('ind2', [[False], pd.Index([False])])
+def test_getitem_bool_index_single(ind1, ind2):
+    # GH#22533
+    idx = MultiIndex.from_tuples([(10, 1)])
+    tm.assert_index_equal(idx[ind1], idx)
+
+    expected = pd.MultiIndex(levels=[np.array([], dtype=np.int64),
+                                     np.array([], dtype=np.int64)],
+                             labels=[[], []])
+    tm.assert_index_equal(idx[ind2], expected)
+
+
 def test_get_loc(idx):
     assert idx.get_loc(('foo', 'two')) == 1
     assert idx.get_loc(('baz', 'two')) == 3

pandas/tests/indexes/test_base.py

@@ -721,6 +721,28 @@ def test_getitem_error(self, indices, itm):
         with pytest.raises(IndexError):
             indices[itm]
 
+    @pytest.mark.parametrize('ind1', [[True] * 5, pd.Index([True] * 5)])
+    @pytest.mark.parametrize('ind2', [[True, False, True, False, False],
+                                      pd.Index([True, False, True, False,
+                                                False])])
+    def test_getitem_bool_index_all(self, ind1, ind2):
+        # GH#22533
+        idx = pd.Index(['a', 'b', 'c', 'd', 'e'], name='idx')
+        tm.assert_index_equal(idx[ind1], idx)
+
+        expected = pd.Index(['a', 'c'], name='idx')
+        tm.assert_index_equal(idx[ind2], expected)
+
+    @pytest.mark.parametrize('ind1', [[True], pd.Index([True])])
+    @pytest.mark.parametrize('ind2', [[False], pd.Index([False])])
+    def test_getitem_bool_index_single(self, ind1, ind2):
+        # GH#22533
+        idx = pd.Index(['a'], name='idx')
+        tm.assert_index_equal(idx[ind1], idx)
+
+        expected = pd.Index([], name='idx')
+        tm.assert_index_equal(idx[ind2], expected)
+
     def test_intersection(self):
         first = self.strIndex[:20]
         second = self.strIndex[:10]

pandas/tests/indexes/test_numeric.py

@@ -843,6 +843,28 @@ def test_join_outer(self):
         tm.assert_numpy_array_equal(lidx, elidx)
         tm.assert_numpy_array_equal(ridx, eridx)
 
+    @pytest.mark.parametrize('ind1', [[True] * 5, pd.Index([True] * 5)])
+    @pytest.mark.parametrize('ind2', [[True, False, True, False, False],
+                                      pd.Index([True, False, True, False,
+                                                False])])
+    def test_getitem_bool_index_all(self, ind1, ind2):
+        # GH#22533
+        idx = pd.Int64Index([1, 2, 3, 4, 5], name='idx')
+        tm.assert_index_equal(idx[ind1], idx)
+
+        expected = pd.Int64Index([1, 3], name='idx')
+        tm.assert_index_equal(idx[ind2], expected)
+
+    @pytest.mark.parametrize('ind1', [[True], pd.Index([True])])
+    @pytest.mark.parametrize('ind2', [[False], pd.Index([False])])
+    def test_getitem_bool_index_single(self, ind1, ind2):
+        # GH#22533
+        idx = pd.Int64Index([1], name='idx')
+        tm.assert_index_equal(idx[ind1], idx)
+
+        expected = pd.Int64Index([], name='idx')
+        tm.assert_index_equal(idx[ind2], expected)
+
 
 class TestUInt64Index(NumericInt):