FIX: boolean fields should still return array

doc/source/whatsnew/v0.20.0.txt

@@ -478,6 +478,8 @@ Accessing datetime fields of Index now return Index
 The several datetime-related attributes (see :ref:`here <timeseries.components>`
 for an overview) of DatetimeIndex, PeriodIndex and TimedeltaIndex previously
 returned numpy arrays, now they will return a new Index object (:issue:`15022`).
+Only in case of a boolean field, still a boolean array is returned to support
+boolean indexing.
 
 Previous behaviour:
 
@@ -498,7 +500,7 @@ New Behavior:
 This has the advantage that specific Index methods are still available on the
 result. On the other hand, this might have backward incompatibilities: e.g.
 compared to numpy arrays, Index objects are not mutable (values cannot be set
-by indexing). To get the original result, you can convert to a nunpy array
+by indexing). To get the original result, you can convert to a numpy array
 explicitly using ``np.asarray(idx.hour)``.
 
 .. _whatsnew_0200.api_breaking.s3:

pandas/tests/indexes/datetimes/test_misc.py

@@ -172,7 +172,7 @@ def test_normalize(self):
 class TestDatetime64(tm.TestCase):
 
     def test_datetimeindex_accessors(self):
-<<<<<<< f2831e2a2074e27e5cd3cfc0728d989742ee4680
+
         dti_naive = DatetimeIndex(freq='D', start=datetime(1998, 1, 1),
                                   periods=365)
         # GH 13303
@@ -258,16 +258,31 @@ def test_datetimeindex_accessors(self):
 
             dti.name = 'name'
 
-            for accessor in ['year', 'month', 'day', 'hour', 'minute', 'second',
-                             'microsecond', 'nanosecond', 'dayofweek', 'dayofyear',
-                             'weekofyear', 'quarter',
-                             'is_month_start', 'is_month_end',
+            # non boolean accessors -> return Index
+            for accessor in ['year', 'month', 'day', 'hour', 'minute',
+                             'second',  'microsecond', 'nanosecond',
+                             'dayofweek', 'dayofyear', 'weekofyear',
+                             'quarter', 'weekday_name']:
+                res = getattr(dti, accessor)
+                assert len(res) == 365
+                assert isinstance(res, Index)
+                assert res.name == 'name'
+
+            # boolean accessors -> return array
+            for accessor in ['is_month_start', 'is_month_end',
                              'is_quarter_start', 'is_quarter_end',
-                             'is_year_start', 'is_year_end', 'weekday_name']:
+                             'is_year_start', 'is_year_end']:
                 res = getattr(dti, accessor)
-                self.assertEqual(len(res), 365)
-                self.assertIsInstance(res, Index)
-                self.assertEqual(res.name, 'name')
+                assert len(res) == 365
+                assert isinstance(res, np.ndarray)
+
+            # test boolean indexing
+            res = dti[dti.is_quarter_start]
+            exp = dti[[0, 90, 181, 273]]
+            tm.assert_index_equal(res, exp)
+            res = dti[dti.is_leap_year]
+            exp = DatetimeIndex([], freq='D', tz=dti.tz, name='name')
+            tm.assert_index_equal(res, exp)
 
         dti = DatetimeIndex(freq='BQ-FEB', start=datetime(1998, 1, 1),
                             periods=4)

pandas/tests/scalar/test_timestamp.py

@@ -597,15 +597,26 @@ def test_nat_fields(self):
     def test_nat_vector_field_access(self):
         idx = DatetimeIndex(['1/1/2000', None, None, '1/4/2000'])
 
+        # non boolean fields
         fields = ['year', 'quarter', 'month', 'day', 'hour', 'minute',
                   'second', 'microsecond', 'nanosecond', 'week', 'dayofyear',
-                  'days_in_month', 'is_leap_year']
+                  'days_in_month']
 
         for field in fields:
             result = getattr(idx, field)
             expected = [getattr(x, field) for x in idx]
             self.assert_index_equal(result, pd.Index(expected))
 
+        # boolean fields
+        fields = ['is_leap_year']
+        # other boolean fields like 'is_month_start' and 'is_month_end'
+        # not yet supported by NaT
+
+        for field in fields:
+            result = getattr(idx, field)
+            expected = [getattr(x, field) for x in idx]
+            self.assert_numpy_array_equal(result, np.array(expected))
+
         s = pd.Series(idx)
 
         for field in fields:

pandas/tseries/index.py

@@ -64,6 +64,7 @@ def f(self):
             if self.tz is not utc:
                 values = self._local_timestamps()
 
+        # boolean accessors -> return array
         if field in ['is_month_start', 'is_month_end',
                      'is_quarter_start', 'is_quarter_end',
                      'is_year_start', 'is_year_end']:
@@ -73,14 +74,15 @@ def f(self):
 
             result = libts.get_start_end_field(values, field, self.freqstr,
                                                month_kw)
-            result = self._maybe_mask_results(result, convert='float64')
+            return self._maybe_mask_results(result, convert='float64')
+        elif field in ['is_leap_year']:
+            # no need to mask NaT
+            return libts.get_date_field(values, field)
 
+        # non-boolean accessors -> return Index
         elif field in ['weekday_name']:
             result = libts.get_date_name_field(values, field)
             result = self._maybe_mask_results(result)
-        elif field in ['is_leap_year']:
-            # no need to mask NaT
-            result = libts.get_date_field(values, field)
         else:
             result = libts.get_date_field(values, field)
             result = self._maybe_mask_results(result, convert='float64')