Add timetz attribute to DatetimeIndex (pandas-dev#22132)

doc/source/api.rst

@@ -545,6 +545,7 @@ These can be accessed like ``Series.dt.<property>``.
 
    Series.dt.date
    Series.dt.time
+   Series.dt.timetz
    Series.dt.year
    Series.dt.month
    Series.dt.day
@@ -1739,6 +1740,7 @@ Time/Date Components
    DatetimeIndex.nanosecond
    DatetimeIndex.date
    DatetimeIndex.time
+   DatetimeIndex.timetz
    DatetimeIndex.dayofyear
    DatetimeIndex.weekofyear
    DatetimeIndex.week

doc/source/timeseries.rst

@@ -724,6 +724,7 @@ There are several time/date properties that one can access from ``Timestamp`` or
     nanosecond,"The nanoseconds of the datetime"
     date,"Returns datetime.date (does not contain timezone information)"
     time,"Returns datetime.time (does not contain timezone information)"
+    timetz,"Returns datetime.time as local time with timezone information"
     dayofyear,"The ordinal day of year"
     weekofyear,"The week ordinal of the year"
     week,"The week ordinal of the year"

doc/source/whatsnew/v0.24.0.txt

@@ -181,6 +181,7 @@ Other Enhancements
   The default compression for ``to_csv``, ``to_json``, and ``to_pickle`` methods has been updated to ``'infer'`` (:issue:`22004`).
 - :func:`to_timedelta` now supports iso-formated timedelta strings (:issue:`21877`)
 - :class:`Series` and :class:`DataFrame` now support :class:`Iterable` in constructor (:issue:`2193`)
+- :class:`DatetimeIndex` gained :attr:`DatetimeIndex.timetz` attribute. Returns local time with timezone information. (:issue:`21358`)
 
 .. _whatsnew_0240.api_breaking:
 

pandas/_libs/tslib.pyx

@@ -72,7 +72,7 @@ cdef inline object create_time_from_ts(
         int64_t value, npy_datetimestruct dts,
         object tz, object freq):
     """ convenience routine to construct a datetime.time from its parts """
-    return time(dts.hour, dts.min, dts.sec, dts.us)
+    return time(dts.hour, dts.min, dts.sec, dts.us, tz)
 
 
 def ints_to_pydatetime(int64_t[:] arr, tz=None, freq=None, box="datetime"):

pandas/core/arrays/datetimes.py

@@ -856,6 +856,14 @@ def time(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="time")
 
+    @property
+    def timetz(self):
+        """
+        Returns numpy array of datetime.time also containing timezone
+        information. The time part of the Timestamps.
+        """
+        return tslib.ints_to_pydatetime(self.asi8, self.tz, box="time")
+
     @property
     def date(self):
         """

pandas/core/indexes/datetimes.py

@@ -170,6 +170,7 @@ class DatetimeIndex(DatetimeArrayMixin, DatelikeOps, TimelikeOps,
     nanosecond
     date
     time
+    timetz
     dayofyear
     weekofyear
     week
@@ -260,7 +261,7 @@ def _add_comparison_methods(cls):
                   'dayofyear', 'quarter', 'days_in_month',
                   'daysinmonth', 'microsecond',
                   'nanosecond']
-    _other_ops = ['date', 'time']
+    _other_ops = ['date', 'time', 'timetz']
     _datetimelike_ops = _field_ops + _object_ops + _bool_ops + _other_ops
     _datetimelike_methods = ['to_period', 'tz_localize',
                              'tz_convert',

pandas/tests/indexes/datetimes/test_timezones.py

@@ -731,6 +731,20 @@ def test_time_accessor(self, dtype):
 
         tm.assert_numpy_array_equal(result, expected)
 
+    def test_timetz_accessor(self, tz_naive_fixture):
+        # GH21358
+        if tz_naive_fixture is not None:
+            tz = dateutil.tz.gettz(tz_naive_fixture)
+        else:
+            tz = None
+
+        expected = np.array([time(10, 20, 30, tzinfo=tz), pd.NaT])
+
+        index = DatetimeIndex(['2018-06-04 10:20:30', pd.NaT], tz=tz)
+        result = index.timetz
+
+        tm.assert_numpy_array_equal(result, expected)
+
     def test_dti_drop_dont_lose_tz(self):
         # GH#2621
         ind = date_range("2012-12-01", periods=10, tz="utc")

pandas/tests/scalar/timestamp/test_timezones.py

@@ -2,7 +2,7 @@
 """
 Tests for Timestamp timezone-related methods
 """
-from datetime import date, timedelta
+from datetime import datetime, date, timedelta
 
 from distutils.version import LooseVersion
 import pytest
@@ -290,3 +290,20 @@ def test_timestamp_add_timedelta_push_over_dst_boundary(self, tz):
         expected = Timestamp('3/11/2012 05:00', tz=tz)
 
         assert result == expected
+
+    def test_timestamp_timetz_equivalent_with_datetime_tz(self,
+                                                          tz_naive_fixture):
+        # GH21358
+        if tz_naive_fixture is not None:
+            tz = dateutil.tz.gettz(tz_naive_fixture)
+        else:
+            tz = None
+
+        stamp = Timestamp('2018-06-04 10:20:30', tz=tz)
+        _datetime = datetime(2018, 6, 4, hour=10,
+                             minute=20, second=30, tzinfo=tz)
+
+        result = stamp.timetz()
+        expected = _datetime.timetz()
+
+        assert result == expected

pandas/tests/series/test_datetime_values.py

@@ -5,7 +5,7 @@
 import calendar
 import pytest
 
-from datetime import datetime, date
+from datetime import datetime, time, date
 
 import numpy as np
 import pandas as pd
@@ -16,6 +16,8 @@
                     PeriodIndex, DatetimeIndex, TimedeltaIndex)
 import pandas.core.common as com
 
+import dateutil
+
 from pandas.util.testing import assert_series_equal
 import pandas.util.testing as tm
 
@@ -459,3 +461,18 @@ def test_datetime_understood(self):
         expected = pd.Series(pd.to_datetime([
             '2011-12-26', '2011-12-27', '2011-12-28']))
         tm.assert_series_equal(result, expected)
+
+    def test_dt_timetz_accessor(self, tz_naive_fixture):
+        # GH21358
+        if tz_naive_fixture is not None:
+            tz = dateutil.tz.gettz(tz_naive_fixture)
+        else:
+            tz = None
+
+        dtindex = pd.DatetimeIndex(['2014-04-04 23:56', '2014-07-18 21:24',
+                                    '2015-11-22 22:14'], tz=tz)
+        s = Series(dtindex)
+        expected = Series([time(23, 56, tzinfo=tz), time(21, 24, tzinfo=tz),
+                           time(22, 14, tzinfo=tz)])
+        result = s.dt.timetz
+        tm.assert_series_equal(result, expected)