BUG: to_datetime not localizing Series when utc=True (pandas-dev#6415)

Modify test case

Author: mroeschke

doc/source/whatsnew/v0.21.0.txt

@@ -260,7 +260,7 @@ Conversion
 
 - Bug in assignment against datetime-like data with ``int`` may incorrectly converte to datetime-like (:issue:`14145`)
 - Bug in assignment against ``int64`` data with ``np.ndarray`` with ``float64`` dtype may keep ``int64`` dtype (:issue:`14001`)
-
+- Bug in :func:`to_datetime` incorrectly localizing dates in `Series` when `utc=True` (:issue:`6415`)
 
 Indexing
 ^^^^^^^^

pandas/core/tools/datetimes.py

@@ -508,6 +508,10 @@ def _convert_listlike(arg, box, format, name=None, tz=tz):
         from pandas import Series
         values = _convert_listlike(arg._values, False, format)
         result = Series(values, index=arg.index, name=arg.name)
+        if utc and isinstance(values, np.ndarray):
+            # If a numpy array is returned from _convert_listlike,
+            # the resulting Series will be naive.
+            result = result.dt.tz_localize('UTC')
     elif isinstance(arg, (ABCDataFrame, MutableMapping)):
         result = _assemble_from_unit_mappings(arg, errors=errors)
     elif isinstance(arg, ABCIndexClass):

pandas/tests/indexes/datetimes/test_tools.py

@@ -270,6 +270,32 @@ def test_to_datetime_utc_is_true(self):
         expected = pd.DatetimeIndex(data=date_range)
         tm.assert_index_equal(result, expected)
 
+        # GH 6415: UTC=True with Series
+        data = ['20100102 121314', '20100102 121315']
+        result = pd.to_datetime(pd.Series(data),
+                                format='%Y%m%d %H%M%S',
+                                utc=True)
+        expected_data = [pd.Timestamp('2010-01-02 12:13:14', tz='utc'),
+                         pd.Timestamp('2010-01-02 12:13:15', tz='utc')]
+        expected = pd.Series(expected_data)
+        tm.assert_series_equal(result, expected)
+
+        # GH 15760 UTC=True with Series
+        ts = 1.5e18
+        result = pd.to_datetime(pd.Series([ts]), utc=True)
+        expected = pd.Series([pd.Timestamp(ts, tz='utc')])
+        tm.assert_series_equal(result, expected)
+
+        test_dates = ['2013-01-01 00:00:00-01:00'] * 10
+        expected_data = [pd.Timestamp('20130101 01:00:00', tz='utc')] * 10
+        expected = pd.Series(expected_data)
+        ser = Series(test_dates)
+        result = pd.to_datetime(ser, utc=True)
+        tm.assert_series_equal(result, expected)
+        ser_naive = Series(test_dates, dtype='datetime64[ns]')
+        result = pd.to_datetime(ser_naive, utc=True)
+        tm.assert_series_equal(result, expected)
+
     def test_to_datetime_tz_psycopg2(self):
 
         # xref 8260

pandas/tests/test_multilevel.py

@@ -2130,7 +2130,7 @@ def test_set_index_datetime(self):
                           '2011-07-19 08:00:00', '2011-07-19 09:00:00'],
              'value': range(6)})
         df.index = pd.to_datetime(df.pop('datetime'), utc=True)
-        df.index = df.index.tz_localize('UTC').tz_convert('US/Pacific')
+        df.index = df.index.tz_convert('US/Pacific')
 
         expected = pd.DatetimeIndex(['2011-07-19 07:00:00',
                                      '2011-07-19 08:00:00',