fix shift

Author: jbrockmendel

pandas/core/arrays/datetimes.py

@@ -19,7 +19,7 @@
     is_extension_type, is_float_dtype, is_int64_dtype, is_object_dtype,
     is_period_dtype, is_string_dtype, is_timedelta64_dtype, pandas_dtype)
 from pandas.core.dtypes.dtypes import DatetimeTZDtype
-from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
+from pandas.core.dtypes.generic import ABCPandasArray, ABCIndexClass, ABCSeries
 from pandas.core.dtypes.missing import isna
 
 from pandas.core import ops
@@ -1644,6 +1644,8 @@ def sequence_to_dt64ns(data, dtype=None, copy=False,
         copy = False
     elif isinstance(data, ABCSeries):
         data = data._values
+    elif isinstance(data, ABCPandasArray):
+        data = data._ndarray
 
     if hasattr(data, "freq"):
         # i.e. DatetimeArray/Index

pandas/core/indexes/datetimelike.py

@@ -666,8 +666,37 @@ def _time_shift(self, periods, freq=None):
 
     @deprecate_kwarg(old_arg_name='n', new_arg_name='periods')
     def shift(self, periods, freq=None):
-        new_values = self._data.shift(periods, freq=freq)
-        return self._simple_new(new_values, name=self.name, freq=self.freq)
+        """
+        Shift index by desired number of time frequency increments.
+
+        This method is for shifting the values of datetime-like indexes
+        by a specified time increment a given number of times.
+
+        Parameters
+        ----------
+        periods : int
+            Number of periods (or increments) to shift by,
+            can be positive or negative.
+
+            .. versionchanged:: 0.24.0
+
+        freq : pandas.DateOffset, pandas.Timedelta or string, optional
+            Frequency increment to shift by.
+            If None, the index is shifted by its own `freq` attribute.
+            Offset aliases are valid strings, e.g., 'D', 'W', 'M' etc.
+
+        Returns
+        -------
+        pandas.DatetimeIndex
+            Shifted index.
+
+        See Also
+        --------
+        Index.shift : Shift values of Index.
+        PeriodIndex.shift : Shift values of PeriodIndex.
+        """
+        result = self._eadata._time_shift(periods, freq=freq)
+        return type(self)(result, name=self.name)
 
 
 def wrap_arithmetic_op(self, other, result):

pandas/core/indexes/datetimes.py

@@ -316,16 +316,18 @@ def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
         if we are passed a non-dtype compat, then coerce using the constructor
         """
         # DatetimeArray._simple_new will accept either i8 or M8[ns] dtypes
-        values = DatetimeArray._simple_new(values, freq=freq, tz=tz)
-
+        if isinstance(values, DatetimeIndex):
+            values = values._data
         dtarr = DatetimeArray._simple_new(values, freq=freq, tz=tz)
+        assert isinstance(dtarr, DatetimeArray)
+
         result = object.__new__(cls)
-        result._data = dtarr._data
-        result._freq = dtarr.freq
+        result._data = dtarr
+        result._freq = dtarr._freq
         result._tz = dtarr.tz
         result.name = name
         # For groupby perf. See note in indexes/base about _index_data
-        result._index_data = values._data
+        result._index_data = dtarr._data
         result._reset_identity()
         return result
 
@@ -335,15 +337,6 @@ def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
     def dtype(self):
         return self._eadata.dtype
 
-    @property
-    def _values(self):
-        # tz-naive -> ndarray
-        # tz-aware -> DatetimeIndex
-        if self.tz is not None:
-            return self
-        else:
-            return self.values
-
     @property
     def tz(self):
         # GH 18595

pandas/core/indexes/timedeltas.py

@@ -245,7 +245,7 @@ def _simple_new(cls, values, name=None, freq=None, dtype=_TD_DTYPE):
         freq = to_offset(freq)
         tdarr = TimedeltaArray._simple_new(values, freq=freq)
         result = object.__new__(cls)
-        result._data = tdarr._data
+        result._data = tdarr
         result._freq = tdarr._freq
         result.name = name
         # For groupby perf. See note in indexes/base about _index_data