BUG: Adjust time values with Period objects in Series.dt.end_time

Author: reidy-p

doc/source/whatsnew/v0.23.0.txt

@@ -342,7 +342,6 @@ Conversion
 - Bug in :class:`Series`` with ``dtype='timedelta64[ns]`` where addition or subtraction of ``TimedeltaIndex`` had results cast to ``dtype='int64'`` (:issue:`17250`)
 - Bug in :class:`TimedeltaIndex` where division by a ``Series`` would return a ``TimedeltaIndex`` instead of a ``Series`` (issue:`19042`)
 - Bug in :class:`Series` with ``dtype='timedelta64[ns]`` where addition or subtraction of ``TimedeltaIndex`` could return a ``Series`` with an incorrect name (issue:`19043`)
--
 
 Indexing
 ^^^^^^^^

pandas/core/indexes/period.py

@@ -633,7 +633,8 @@ def start_time(self):
 
     @property
     def end_time(self):
-        return self.to_timestamp(how='end')
+        data = (self + 1).start_time.values.astype(int) - 1
+        return DatetimeIndex(data=data)
 
     def _mpl_repr(self):
         # how to represent ourselves to matplotlib

pandas/tests/indexes/period/test_period.py

@@ -462,8 +462,29 @@ def test_start_time(self):
     def test_end_time(self):
         index = PeriodIndex(freq='M', start='2016-01-01', end='2016-05-31')
         expected_index = date_range('2016-01-01', end='2016-05-31', freq='M')
+        expected_index = expected_index.shift(1, freq='D').shift(-1, freq='ns')
         tm.assert_index_equal(index.end_time, expected_index)
 
+    @pytest.mark.parametrize('input_vals', [
+        [Period('2016-01', freq='M'), Period('2016-02', freq='M')],
+        [Period('2016-01-01', freq='D'), Period('2016-01-02', freq='D')],
+        [Period('2016-01-01 00:00:00', freq='H'),
+         Period('2016-01-01 01:00:00', freq='H')],
+        [Period('2016-01-01 00:00:00', freq='M'),
+         Period('2016-01-01 00:01:00', freq='M')],
+        [Period('2016-01-01 00:00:00', freq='S'),
+         Period('2016-01-01 00:00:01', freq='S')]
+    ])
+    def test_end_time_timevalues(self, input_vals):
+        # GH 17157
+        # Check that the time part of the Period is adjusted by end_time
+        # when using the dt accessor on a Series
+
+        s = Series(input_vals)
+        result = s.dt.end_time
+        expected = s.apply(lambda x: x.end_time)
+        tm.assert_series_equal(result, expected)
+
     def test_index_duplicate_periods(self):
         # monotonic
         idx = PeriodIndex([2000, 2007, 2007, 2009, 2009], freq='A-JUN')