BUG: DatetimeTZBlock can't assign values near dst boundary

Author: sinhrks

Diff for: doc/source/whatsnew/v0.19.0.txt

@@ -1559,7 +1559,7 @@ Bug Fixes
 - Bug in ``Series`` flexible arithmetic methods (like ``.add()``) raises ``ValueError`` when ``axis=None`` (:issue:`13894`)
 - Bug in ``DataFrame.to_csv()`` with ``MultiIndex`` columns in which a stray empty line was added (:issue:`6618`)
 - Bug in ``DatetimeIndex``, ``TimedeltaIndex`` and ``PeriodIndex.equals()`` may return ``True`` when input isn't ``Index`` but contains the same values (:issue:`13107`)
-
+- Bug in assignment against datetime with timezone may not work if it contains datetime near DST boundary (:issue:`14146`)
 
 - Bug in ``Index`` raises ``KeyError`` displaying incorrect column when column is not in the df and columns contains duplicate values (:issue:`13822`)
 - Bug in ``Period`` and ``PeriodIndex`` creating wrong dates when frequency has combined offset aliases (:issue:`13874`)

Diff for: pandas/core/internals.py

@@ -1487,7 +1487,10 @@ def putmask(self, mask, new, align=True, inplace=False, axis=0,
         -------
         a new block(s), the result of the putmask
         """
-        new_values = self.values if inplace else self.values.copy()
+
+        # use block's copy logic.
+        # .values may be an Index which does shallow copy by default
+        new_values = self.values if inplace else self.copy().values
         new_values, _, new, _ = self._try_coerce_args(new_values, new)
 
         if isinstance(new, np.ndarray) and len(new) == len(mask):
@@ -2314,7 +2317,7 @@ def __init__(self, values, placement, ndim=2, **kwargs):
         if dtype is not None:
             if isinstance(dtype, compat.string_types):
                 dtype = DatetimeTZDtype.construct_from_string(dtype)
-            values = values.tz_localize('UTC').tz_convert(dtype.tz)
+            values = values._shallow_copy(tz=dtype.tz)
 
         if values.tz is None:
             raise ValueError("cannot create a DatetimeTZBlock without a tz")
@@ -2381,12 +2384,14 @@ def _try_coerce_args(self, values, other):
         base-type values, values mask, base-type other, other mask
         """
         values_mask = _block_shape(isnull(values), ndim=self.ndim)
-        values = _block_shape(values.tz_localize(None).asi8, ndim=self.ndim)
+        # asi8 is a view, needs copy
+        values = _block_shape(values.asi8, ndim=self.ndim)
         other_mask = False
 
         if isinstance(other, ABCSeries):
             other = self._holder(other)
             other_mask = isnull(other)
+
         if isinstance(other, bool):
             raise TypeError
         elif is_null_datelike_scalar(other):
@@ -2395,7 +2400,7 @@ def _try_coerce_args(self, values, other):
         elif isinstance(other, self._holder):
             if other.tz != self.values.tz:
                 raise ValueError("incompatible or non tz-aware value")
-            other = other.tz_localize(None).asi8
+            other = other.asi8
             other_mask = isnull(other)
         elif isinstance(other, (np.datetime64, datetime, date)):
             other = lib.Timestamp(other)
@@ -2405,7 +2410,7 @@ def _try_coerce_args(self, values, other):
             if tz is None or str(tz) != str(self.values.tz):
                 raise ValueError("incompatible or non tz-aware value")
             other_mask = isnull(other)
-            other = other.tz_localize(None).value
+            other = other.value
 
         return values, values_mask, other, other_mask
 
@@ -2415,12 +2420,12 @@ def _try_coerce_result(self, result):
             if result.dtype.kind in ['i', 'f', 'O']:
                 result = result.astype('M8[ns]')
         elif isinstance(result, (np.integer, np.float, np.datetime64)):
-            result = lib.Timestamp(result).tz_localize(self.values.tz)
+            result = lib.Timestamp(result, tz=self.values.tz)
         if isinstance(result, np.ndarray):
             # allow passing of > 1dim if its trivial
             if result.ndim > 1:
                 result = result.reshape(len(result))
-            result = self._holder(result).tz_localize(self.values.tz)
+            result = self.values._shallow_copy(result)
 
         return result
 

Diff for: pandas/tests/indexing/test_coercion.py

@@ -229,7 +229,7 @@ def test_setitem_series_datetime64tz(self):
         # datetime64 + int -> object
         # ToDo: The result must be object
         exp = pd.Series([pd.Timestamp('2011-01-01', tz=tz),
-                         pd.Timestamp(1).tz_localize(tz),
+                         pd.Timestamp(1, tz=tz),
                          pd.Timestamp('2011-01-03', tz=tz),
                          pd.Timestamp('2011-01-04', tz=tz)])
         self._assert_setitem_series_conversion(obj, 1, exp,
@@ -1038,7 +1038,7 @@ def test_fillna_series_datetime64tz(self):
         # datetime64tz + int => datetime64tz
         # ToDo: must be object
         exp = pd.Series([pd.Timestamp('2011-01-01', tz=tz),
-                         pd.Timestamp(1).tz_localize(tz=tz),
+                         pd.Timestamp(1, tz=tz),
                          pd.Timestamp('2011-01-03', tz=tz),
                          pd.Timestamp('2011-01-04', tz=tz)])
         self._assert_fillna_conversion(obj, 1, exp,

Diff for: pandas/tests/series/test_indexing.py

@@ -776,6 +776,89 @@ def test_ix_getitem_iterator(self):
         result = self.series.ix[idx]
         assert_series_equal(result, self.series[:10])
 
+    def test_setitem_with_tz(self):
+        for tz in ['US/Eastern', 'UTC', 'Asia/Tokyo']:
+            orig = pd.Series(pd.date_range('2016-01-01', freq='H', periods=3,
+                                           tz=tz))
+            self.assertEqual(orig.dtype, 'datetime64[ns, {0}]'.format(tz))
+
+            # scalar
+            s = orig.copy()
+            s[1] = pd.Timestamp('2011-01-01', tz=tz)
+            exp = pd.Series([pd.Timestamp('2016-01-01 00:00', tz=tz),
+                             pd.Timestamp('2011-01-01 00:00', tz=tz),
+                             pd.Timestamp('2016-01-01 02:00', tz=tz)])
+            tm.assert_series_equal(s, exp)
+
+            s = orig.copy()
+            s.loc[1] = pd.Timestamp('2011-01-01', tz=tz)
+            tm.assert_series_equal(s, exp)
+
+            s = orig.copy()
+            s.iloc[1] = pd.Timestamp('2011-01-01', tz=tz)
+            tm.assert_series_equal(s, exp)
+
+            # vector
+            vals = pd.Series([pd.Timestamp('2011-01-01', tz=tz),
+                              pd.Timestamp('2012-01-01', tz=tz)], index=[1, 2])
+            self.assertEqual(vals.dtype, 'datetime64[ns, {0}]'.format(tz))
+
+            s[[1, 2]] = vals
+            exp = pd.Series([pd.Timestamp('2016-01-01 00:00', tz=tz),
+                             pd.Timestamp('2011-01-01 00:00', tz=tz),
+                             pd.Timestamp('2012-01-01 00:00', tz=tz)])
+            tm.assert_series_equal(s, exp)
+
+            s = orig.copy()
+            s.loc[[1, 2]] = vals
+            tm.assert_series_equal(s, exp)
+
+            s = orig.copy()
+            s.iloc[[1, 2]] = vals
+            tm.assert_series_equal(s, exp)
+
+    def test_setitem_with_tz_dst(self):
+        # GH XXX
+        tz = 'US/Eastern'
+        orig = pd.Series(pd.date_range('2016-11-06', freq='H', periods=3,
+                                       tz=tz))
+        self.assertEqual(orig.dtype, 'datetime64[ns, {0}]'.format(tz))
+
+        # scalar
+        s = orig.copy()
+        s[1] = pd.Timestamp('2011-01-01', tz=tz)
+        exp = pd.Series([pd.Timestamp('2016-11-06 00:00', tz=tz),
+                         pd.Timestamp('2011-01-01 00:00', tz=tz),
+                         pd.Timestamp('2016-11-06 02:00', tz=tz)])
+        tm.assert_series_equal(s, exp)
+
+        s = orig.copy()
+        s.loc[1] = pd.Timestamp('2011-01-01', tz=tz)
+        tm.assert_series_equal(s, exp)
+
+        s = orig.copy()
+        s.iloc[1] = pd.Timestamp('2011-01-01', tz=tz)
+        tm.assert_series_equal(s, exp)
+
+        # vector
+        vals = pd.Series([pd.Timestamp('2011-01-01', tz=tz),
+                          pd.Timestamp('2012-01-01', tz=tz)], index=[1, 2])
+        self.assertEqual(vals.dtype, 'datetime64[ns, {0}]'.format(tz))
+
+        s[[1, 2]] = vals
+        exp = pd.Series([pd.Timestamp('2016-11-06 00:00', tz=tz),
+                         pd.Timestamp('2011-01-01 00:00', tz=tz),
+                         pd.Timestamp('2012-01-01 00:00', tz=tz)])
+        tm.assert_series_equal(s, exp)
+
+        s = orig.copy()
+        s.loc[[1, 2]] = vals
+        tm.assert_series_equal(s, exp)
+
+        s = orig.copy()
+        s.iloc[[1, 2]] = vals
+        tm.assert_series_equal(s, exp)
+
     def test_where(self):
         s = Series(np.random.randn(5))
         cond = s > 0

Diff for: pandas/tests/series/test_misc_api.py

@@ -241,7 +241,6 @@ def test_copy(self):
                 self.assertTrue(np.isnan(s2[0]))
                 self.assertFalse(np.isnan(s[0]))
             else:
-
                 # we DID modify the original Series
                 self.assertTrue(np.isnan(s2[0]))
                 self.assertTrue(np.isnan(s[0]))
@@ -252,6 +251,7 @@ def test_copy(self):
         expected2 = Series([Timestamp('1999/01/01', tz='UTC')])
 
         for deep in [None, False, True]:
+
             s = Series([Timestamp('2012/01/01', tz='UTC')])
 
             if deep is None:
@@ -263,11 +263,13 @@ def test_copy(self):
 
             # default deep is True
             if deep is None or deep is True:
-                assert_series_equal(s, expected)
+                # Did not modify original Series
                 assert_series_equal(s2, expected2)
+                assert_series_equal(s, expected)
             else:
-                assert_series_equal(s, expected2)
+                # we DID modify the original Series
                 assert_series_equal(s2, expected2)
+                assert_series_equal(s, expected2)
 
     def test_axis_alias(self):
         s = Series([1, 2, np.nan])

Diff for: pandas/tests/series/test_missing.py

@@ -130,99 +130,125 @@ def test_datetime64_fillna(self):
     def test_datetime64_tz_fillna(self):
         for tz in ['US/Eastern', 'Asia/Tokyo']:
             # DatetimeBlock
-            s = Series([Timestamp('2011-01-01 10:00'), pd.NaT, Timestamp(
-                '2011-01-03 10:00'), pd.NaT])
+            s = Series([Timestamp('2011-01-01 10:00'), pd.NaT,
+                        Timestamp('2011-01-03 10:00'), pd.NaT])
+            null_loc = pd.Series([False, True, False, True])
+
             result = s.fillna(pd.Timestamp('2011-01-02 10:00'))
-            expected = Series([Timestamp('2011-01-01 10:00'), Timestamp(
-                '2011-01-02 10:00'), Timestamp('2011-01-03 10:00'), Timestamp(
-                    '2011-01-02 10:00')])
+            expected = Series([Timestamp('2011-01-01 10:00'),
+                               Timestamp('2011-01-02 10:00'),
+                               Timestamp('2011-01-03 10:00'),
+                               Timestamp('2011-01-02 10:00')])
             self.assert_series_equal(expected, result)
+            # check s is not changed
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna(pd.Timestamp('2011-01-02 10:00', tz=tz))
-            expected = Series([Timestamp('2011-01-01 10:00'), Timestamp(
-                '2011-01-02 10:00', tz=tz), Timestamp('2011-01-03 10:00'),
-                Timestamp('2011-01-02 10:00', tz=tz)])
+            expected = Series([Timestamp('2011-01-01 10:00'),
+                               Timestamp('2011-01-02 10:00', tz=tz),
+                               Timestamp('2011-01-03 10:00'),
+                               Timestamp('2011-01-02 10:00', tz=tz)])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna('AAA')
             expected = Series([Timestamp('2011-01-01 10:00'), 'AAA',
                                Timestamp('2011-01-03 10:00'), 'AAA'],
                               dtype=object)
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna({1: pd.Timestamp('2011-01-02 10:00', tz=tz),
                                3: pd.Timestamp('2011-01-04 10:00')})
-            expected = Series([Timestamp('2011-01-01 10:00'), Timestamp(
-                '2011-01-02 10:00', tz=tz), Timestamp('2011-01-03 10:00'),
-                Timestamp('2011-01-04 10:00')])
+            expected = Series([Timestamp('2011-01-01 10:00'),
+                               Timestamp('2011-01-02 10:00', tz=tz),
+                               Timestamp('2011-01-03 10:00'),
+                               Timestamp('2011-01-04 10:00')])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna({1: pd.Timestamp('2011-01-02 10:00'),
                                3: pd.Timestamp('2011-01-04 10:00')})
-            expected = Series([Timestamp('2011-01-01 10:00'), Timestamp(
-                '2011-01-02 10:00'), Timestamp('2011-01-03 10:00'), Timestamp(
-                    '2011-01-04 10:00')])
+            expected = Series([Timestamp('2011-01-01 10:00'),
+                               Timestamp('2011-01-02 10:00'),
+                               Timestamp('2011-01-03 10:00'),
+                               Timestamp('2011-01-04 10:00')])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             # DatetimeBlockTZ
             idx = pd.DatetimeIndex(['2011-01-01 10:00', pd.NaT,
                                     '2011-01-03 10:00', pd.NaT], tz=tz)
             s = pd.Series(idx)
+            self.assertEqual(s.dtype, 'datetime64[ns, {0}]'.format(tz))
+            self.assert_series_equal(pd.isnull(s), null_loc)
+
             result = s.fillna(pd.Timestamp('2011-01-02 10:00'))
-            expected = Series([Timestamp('2011-01-01 10:00', tz=tz), Timestamp(
-                '2011-01-02 10:00'), Timestamp('2011-01-03 10:00', tz=tz),
-                Timestamp('2011-01-02 10:00')])
+            expected = Series([Timestamp('2011-01-01 10:00', tz=tz),
+                               Timestamp('2011-01-02 10:00'),
+                               Timestamp('2011-01-03 10:00', tz=tz),
+                               Timestamp('2011-01-02 10:00')])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna(pd.Timestamp('2011-01-02 10:00', tz=tz))
             idx = pd.DatetimeIndex(['2011-01-01 10:00', '2011-01-02 10:00',
                                     '2011-01-03 10:00', '2011-01-02 10:00'],
                                    tz=tz)
             expected = Series(idx)
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
-            result = s.fillna(pd.Timestamp(
-                '2011-01-02 10:00', tz=tz).to_pydatetime())
+            result = s.fillna(pd.Timestamp('2011-01-02 10:00',
+                                           tz=tz).to_pydatetime())
             idx = pd.DatetimeIndex(['2011-01-01 10:00', '2011-01-02 10:00',
                                     '2011-01-03 10:00', '2011-01-02 10:00'],
                                    tz=tz)
             expected = Series(idx)
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna('AAA')
             expected = Series([Timestamp('2011-01-01 10:00', tz=tz), 'AAA',
                                Timestamp('2011-01-03 10:00', tz=tz), 'AAA'],
                               dtype=object)
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna({1: pd.Timestamp('2011-01-02 10:00', tz=tz),
                                3: pd.Timestamp('2011-01-04 10:00')})
-            expected = Series([Timestamp('2011-01-01 10:00', tz=tz), Timestamp(
-                '2011-01-02 10:00', tz=tz), Timestamp(
-                    '2011-01-03 10:00', tz=tz), Timestamp('2011-01-04 10:00')])
+            expected = Series([Timestamp('2011-01-01 10:00', tz=tz),
+                               Timestamp('2011-01-02 10:00', tz=tz),
+                               Timestamp('2011-01-03 10:00', tz=tz),
+                               Timestamp('2011-01-04 10:00')])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna({1: pd.Timestamp('2011-01-02 10:00', tz=tz),
                                3: pd.Timestamp('2011-01-04 10:00', tz=tz)})
-            expected = Series([Timestamp('2011-01-01 10:00', tz=tz), Timestamp(
-                '2011-01-02 10:00', tz=tz), Timestamp(
-                    '2011-01-03 10:00', tz=tz), Timestamp('2011-01-04 10:00',
-                                                          tz=tz)])
+            expected = Series([Timestamp('2011-01-01 10:00', tz=tz),
+                               Timestamp('2011-01-02 10:00', tz=tz),
+                               Timestamp('2011-01-03 10:00', tz=tz),
+                               Timestamp('2011-01-04 10:00', tz=tz)])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             # filling with a naive/other zone, coerce to object
             result = s.fillna(Timestamp('20130101'))
-            expected = Series([Timestamp('2011-01-01 10:00', tz=tz), Timestamp(
-                '2013-01-01'), Timestamp('2011-01-03 10:00', tz=tz), Timestamp(
-                    '2013-01-01')])
+            expected = Series([Timestamp('2011-01-01 10:00', tz=tz),
+                               Timestamp('2013-01-01'),
+                               Timestamp('2011-01-03 10:00', tz=tz),
+                               Timestamp('2013-01-01')])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
             result = s.fillna(Timestamp('20130101', tz='US/Pacific'))
             expected = Series([Timestamp('2011-01-01 10:00', tz=tz),
                                Timestamp('2013-01-01', tz='US/Pacific'),
                                Timestamp('2011-01-03 10:00', tz=tz),
                                Timestamp('2013-01-01', tz='US/Pacific')])
             self.assert_series_equal(expected, result)
+            self.assert_series_equal(pd.isnull(s), null_loc)
 
     def test_fillna_int(self):
         s = Series(np.random.randint(-100, 100, 50))