Fixed: where

Author: TomAugspurger

pandas/core/arrays/datetimelike.py

@@ -600,6 +600,20 @@ def take(self, indices, allow_fill=False, fill_value=None):
 
         return type(self)(new_values, dtype=self.dtype)
 
+    def where(self, cond, other):
+        i8 = self.asi8
+        if lib.is_scalar(other):
+            if isna(other):
+                other = iNaT
+            elif isinstance(other, self._scalar_type):
+                self._check_compatible_with(other)
+                other = other.ordinal
+        elif isinstance(other, type(self)):
+            self._check_compatible_with(other)
+            other = other.asi8
+        result = np.where(cond, i8, other)
+        return type(self)._simple_new(result, dtype=self.dtype)
+
     @classmethod
     def _concat_same_type(cls, to_concat):
         dtypes = {x.dtype for x in to_concat}

pandas/core/arrays/datetimes.py

@@ -205,7 +205,9 @@ class DatetimeArrayMixin(dtl.DatetimeLikeArrayMixin,
     _freq = None
 
     @classmethod
-    def _simple_new(cls, values, freq=None, tz=None):
+    def _simple_new(cls, values, freq=None, tz=None, dtype=None):
+        # TODO: can we make this signature just
+        # values, dtype, freq?
         """
         we require the we have a dtype compat for the values
         if we are passed a non-dtype compat, then coerce using the constructor
@@ -218,6 +220,8 @@ def _simple_new(cls, values, freq=None, tz=None):
             values = values.view('M8[ns]')
 
         assert values.dtype == 'M8[ns]', values.dtype
+        if tz is None and dtype:
+            tz = getattr(dtype, 'tz')
 
         result = object.__new__(cls)
         result._data = values

pandas/core/arrays/period.py

@@ -4,7 +4,6 @@
 
 import numpy as np
 
-from pandas._libs import lib
 from pandas._libs.tslibs import NaT, iNaT, period as libperiod
 from pandas._libs.tslibs.fields import isleapyear_arr
 from pandas._libs.tslibs.period import (
@@ -348,22 +347,6 @@ def to_timestamp(self, freq=None, how='start'):
     # --------------------------------------------------------------------
     # Array-like / EA-Interface Methods
 
-    def where(self, cond, other):
-        # TODO(DatetimeArray): move to DatetimeLikeArrayMixin
-        # n.b. _ndarray_values candidate.
-        i8 = self.asi8
-        if lib.is_scalar(other):
-            if isna(other):
-                other = iNaT
-            elif isinstance(other, Period):
-                self._check_compatible_with(other)
-                other = other.ordinal
-        elif isinstance(other, type(self)):
-            self._check_compatible_with(other)
-            other = other.asi8
-        result = np.where(cond, i8, other)
-        return type(self)._simple_new(result, dtype=self.dtype)
-
     def _formatter(self, boxed=False):
         if boxed:
             return str

pandas/core/internals/blocks.py

@@ -31,7 +31,6 @@
 from pandas.core.dtypes.generic import (
     ABCDataFrame, ABCDatetimeIndex, ABCExtensionArray, ABCIndexClass,
     ABCSeries)
-from pandas.core.dtypes.inference import is_scalar
 from pandas.core.dtypes.missing import (
     _isna_compat, array_equivalent, is_null_datelike_scalar, isna, notna)
 
@@ -3089,7 +3088,7 @@ def setitem(self, indexer, value):
         return_object = (
             (maybe_tz
              and not timezones.tz_compare(self.values.tz, maybe_tz)) or
-            (is_scalar(value)
+            (lib.is_scalar(value)
              and not isna(value)
              and not value == tslib.iNaT
              and not (isinstance(value, self.values._scalar_type) and

pandas/tests/frame/test_indexing.py

@@ -3075,7 +3075,6 @@ def test_where_callable(self):
         tm.assert_frame_equal(result,
                               (df + 2).where((df + 2) > 8, (df + 2) + 10))
 
-    @pytest.mark.xfail(reason="TODO-where", strict=False)
     def test_where_tz_values(self, tz_naive_fixture):
         df1 = DataFrame(DatetimeIndex(['20150101', '20150102', '20150103'],
                                       tz=tz_naive_fixture),

pandas/tests/indexes/timedeltas/test_timedelta.py

@@ -28,10 +28,6 @@ def setup_method(self, method):
     def create_index(self):
         return pd.to_timedelta(range(5), unit='d') + pd.offsets.Hour(1)
 
-    @pytest.mark.skip(reason="TODO-where")
-    def test_where(self, klass):
-        return super().test_where(klass)
-
     def test_numeric_compat(self):
         # Dummy method to override super's version; this test is now done
         # in test_arithmetic.py

pandas/tests/series/test_combine_concat.py

@@ -198,7 +198,10 @@ def get_result_type(dtype, dtype2):
                                     ]).dtype
                 assert result.kind == expected
 
-    @pytest.mark.xfail(resson="TODO-where", strict=False)
+    @pytest.mark.xfail(resson="TODO-where-internals", strict=False)
+    # Something strange with internals shapes.
+    # After reindexing in combine_first, our tz-block mananger is
+    # (maybe?) in a bad state.
     def test_combine_first_dt_tz_values(self, tz_naive_fixture):
         ser1 = pd.Series(pd.DatetimeIndex(['20150101', '20150102', '20150103'],
                                           tz=tz_naive_fixture),