Some cleanups

Author: TomAugspurger

pandas/core/arrays/datetimelike.py

@@ -99,7 +99,19 @@ def _scalar_type(self):
         raise AbstractMethodError(self)
 
     def _scalar_from_string(self, value):
-        # type: (str) -> Union[Period, Timestamp, Timedelta]
+        # type: (str) -> Union[Period, Timestamp, Timedelta, NaT]
+        """
+        Construct a scalar type from a string.
+
+        Parameters
+        ----------
+        value : str
+
+        Returns
+        -------
+        Period, Timestamp, or Timedelt, or NaT
+            Whatever the type of ``self._scalar_type`` is.
+        """
         raise AbstractMethodError(self)
 
     def _unbox_scalar(self, value):
@@ -1096,7 +1108,7 @@ def _time_shift(self, periods, freq=None):
                 freq = frequencies.to_offset(freq)
             offset = periods * freq
             result = self + offset
-            if hasattr(self, 'tz'):
+            if getattr(self, 'tz', None):
                 result._dtype = DatetimeTZDtype(tz=self.tz)
             return result
 

pandas/core/arrays/datetimes.py

@@ -302,7 +302,7 @@ def __init__(self, values, dtype=_NS_DTYPE, freq=None, copy=False):
         if getattr(dtype, 'tz', None):
             # https://github.com/pandas-dev/pandas/issues/18595
             # Ensure that we have a standard timezone for pytz objects.
-            # Without this, thins like adding an array of timedeltas and
+            # Without this, things like adding an array of timedeltas and
             # a  tz-aware Timestamp (with a tz specific to its datetime) will
             # be incorrect(ish?) for the array as a whole
             dtype = DatetimeTZDtype(tz=timezones.tz_standardize(dtype.tz))

pandas/core/arrays/period.py

@@ -240,7 +240,10 @@ def _unbox_scalar(self, value):
         elif isinstance(value, self._scalar_type):
             return value.ordinal
         else:
-            raise ValueError("'value' should be a Period")
+            msg = (
+                "'value' should be a Period. Got '{}' instead."
+            )
+            raise ValueError(msg.format(value))
 
     def _scalar_from_string(self, value):
         # type: (str) -> Period

pandas/core/indexes/datetimelike.py

@@ -146,9 +146,6 @@ def _evaluate_compare(self, other, op):
 
     def _ensure_localized(self, arg, ambiguous='raise', nonexistent='raise',
                           from_utc=False):
-        # This is a strange one. It seems like for for non-datetimetz
-        # we just pass arg (an ndarray) through, while for datetimetz
-        # we want to return a DatetimeIndex?
         result = self._values._ensure_localized(arg,
                                                 ambiguous=ambiguous,
                                                 nonexistent=nonexistent,

pandas/core/internals/blocks.py

@@ -8,7 +8,7 @@
 import numpy as np
 
 from pandas._libs import internals as libinternals, lib, tslib, tslibs
-from pandas._libs.tslibs import Timedelta, conversion, timezones
+from pandas._libs.tslibs import Timedelta, conversion
 import pandas.compat as compat
 from pandas.compat import range, zip
 from pandas.errors import AbstractMethodError
@@ -3156,23 +3156,13 @@ def setitem(self, indexer, value):
         # https://github.com/pandas-dev/pandas/issues/24020
         # Need a dedicated setitem until #24020 (type promotion in setitem
         # for extension arrays) is designed and implemented.
-        maybe_tz = getattr(value, 'tz', None)
-        return_object = (
-            (maybe_tz
-             and not timezones.tz_compare(self.values.tz, maybe_tz)) or
-            (lib.is_scalar(value)
-             and not isna(value)
-             and not value == tslib.iNaT
-             and not (isinstance(value, self.values._scalar_type) and
-                      timezones.tz_compare(self.values.tz, maybe_tz)))
-        )
-
-        if return_object:
+        try:
+            return super(DatetimeTZBlock, self).setitem(indexer, value)
+        except ValueError:
             newb = make_block(self.values.astype(object),
                               placement=self.mgr_locs,
                               klass=ObjectBlock,)
             return newb.setitem(indexer, value)
-        return super(DatetimeTZBlock, self).setitem(indexer, value)
 
 
 # -----------------------------------------------------------------

pandas/tests/series/test_datetime_values.py

@@ -555,3 +555,12 @@ def test_setitem_with_string_index(self):
         x['Date'] = date.today()
         assert x.Date == date.today()
         assert x['Date'] == date.today()
+
+    def test_setitem_with_different_tz(self):
+        ser = pd.Series(pd.date_range('2000', periods=2, tz="US/Central"))
+        ser[0] = pd.Timestamp("2000", tz='US/Eastern')
+        expected = pd.Series([
+            pd.Timestamp("2000-01-01 00:00:00-05:00", tz="US/Eastern"),
+            pd.Timestamp("2000-01-02 00:00:00-06:00", tz="US/Central"),
+        ], dtype=object)
+        tm.assert_series_equal(ser, expected)