BUG: Series.view from int64 to datetimelike

pandas/core/arrays/_mixins.py

@@ -16,6 +16,8 @@
 from pandas._libs import lib
 from pandas._libs.arrays import NDArrayBacked
 from pandas._typing import (
+    ArrayLike,
+    Dtype,
     F,
     PositionalIndexer2D,
     PositionalIndexerTuple,
@@ -34,8 +36,15 @@
     validate_insert_loc,
 )
 
-from pandas.core.dtypes.common import is_dtype_equal
-from pandas.core.dtypes.dtypes import ExtensionDtype
+from pandas.core.dtypes.common import (
+    is_dtype_equal,
+    pandas_dtype,
+)
+from pandas.core.dtypes.dtypes import (
+    DatetimeTZDtype,
+    ExtensionDtype,
+    PeriodDtype,
+)
 from pandas.core.dtypes.missing import array_equivalent
 
 from pandas.core import missing
@@ -101,6 +110,41 @@ def _validate_scalar(self, value):
 
     # ------------------------------------------------------------------------
 
+    def view(self, dtype: Dtype | None = None) -> ArrayLike:
+        # We handle datetime64, datetime64tz, timedelta64, and period
+        #  dtypes here. Everything else we pass through to the underlying
+        #  ndarray.
+        if dtype is None or dtype is self.dtype:
+            return self._from_backing_data(self._ndarray)
+
+        if isinstance(dtype, type):
+            # we sometimes pass non-dtype objects, e.g np.ndarray;
+            #  pass those through to the underlying ndarray
+            return self._ndarray.view(dtype)
+
+        dtype = pandas_dtype(dtype)
+        arr = self._ndarray
+
+        if isinstance(dtype, (PeriodDtype, DatetimeTZDtype)):
+            cls = dtype.construct_array_type()
+            return cls(arr.view("i8"), dtype=dtype)
+        elif dtype == "M8[ns]":
+            from pandas.core.arrays import DatetimeArray
+
+            return DatetimeArray(arr.view("i8"), dtype=dtype)
+        elif dtype == "m8[ns]":
+            from pandas.core.arrays import TimedeltaArray
+
+            return TimedeltaArray(arr.view("i8"), dtype=dtype)
+
+        # error: Incompatible return value type (got "ndarray", expected
+        # "ExtensionArray")
+        # error: Argument "dtype" to "view" of "_ArrayOrScalarCommon" has incompatible
+        # type "Union[ExtensionDtype, dtype[Any]]"; expected "Union[dtype[Any], None,
+        # type, _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
+        # Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
+        return arr.view(dtype=dtype)  # type: ignore[return-value,arg-type]
+
     def take(
         self: NDArrayBackedExtensionArrayT,
         indices: TakeIndexer,

pandas/core/arrays/datetimelike.py

@@ -85,11 +85,7 @@
     is_unsigned_integer_dtype,
     pandas_dtype,
 )
-from pandas.core.dtypes.dtypes import (
-    DatetimeTZDtype,
-    ExtensionDtype,
-    PeriodDtype,
-)
+from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.missing import (
     is_valid_na_for_dtype,
     isna,
@@ -461,36 +457,9 @@ def view(self, dtype: Dtype | None = ...) -> ArrayLike:
         ...
 
     def view(self, dtype: Dtype | None = None) -> ArrayLike:
-        # We handle datetime64, datetime64tz, timedelta64, and period
-        #  dtypes here. Everything else we pass through to the underlying
-        #  ndarray.
-        if dtype is None or dtype is self.dtype:
-            return type(self)(self._ndarray, dtype=self.dtype)
-
-        if isinstance(dtype, type):
-            # we sometimes pass non-dtype objects, e.g np.ndarray;
-            #  pass those through to the underlying ndarray
-            return self._ndarray.view(dtype)
-
-        dtype = pandas_dtype(dtype)
-        if isinstance(dtype, (PeriodDtype, DatetimeTZDtype)):
-            cls = dtype.construct_array_type()
-            return cls(self.asi8, dtype=dtype)
-        elif dtype == "M8[ns]":
-            from pandas.core.arrays import DatetimeArray
-
-            return DatetimeArray(self.asi8, dtype=dtype)
-        elif dtype == "m8[ns]":
-            from pandas.core.arrays import TimedeltaArray
-
-            return TimedeltaArray(self.asi8, dtype=dtype)
-        # error: Incompatible return value type (got "ndarray", expected
-        # "ExtensionArray")
-        # error: Argument "dtype" to "view" of "_ArrayOrScalarCommon" has incompatible
-        # type "Union[ExtensionDtype, dtype[Any]]"; expected "Union[dtype[Any], None,
-        # type, _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
-        # Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
-        return self._ndarray.view(dtype=dtype)  # type: ignore[return-value,arg-type]
+        # we need to explicitly call super() method as long as the `@overload`s
+        #  are present in this file.
+        return super().view(dtype)
 
     # ------------------------------------------------------------------
     # ExtensionArray Interface

pandas/core/indexes/base.py

@@ -947,7 +947,6 @@ def view(self, cls=None):
                     # e.g. m8[s]
                     return self._data.view(cls)
 
-                arr = self._data.view("i8")
                 idx_cls = self._dtype_to_subclass(dtype)
                 arr_cls = idx_cls._data_cls
                 arr = arr_cls(self._data.view("i8"), dtype=dtype)

pandas/core/series.py

@@ -802,9 +802,11 @@ def view(self, dtype: Dtype | None = None) -> Series:
         4      2
         dtype: int8
         """
-        return self._constructor(
-            self._values.view(dtype), index=self.index
-        ).__finalize__(self, method="view")
+        # self.array instead of self._values so we piggyback on PandasArray
+        #  implementation
+        res_values = self.array.view(dtype)
+        res_ser = self._constructor(res_values, index=self.index)
+        return res_ser.__finalize__(self, method="view")
 
     # ----------------------------------------------------------------------
     # NDArray Compat

pandas/tests/series/methods/test_view.py

@@ -11,6 +11,18 @@
 
 
 class TestView:
+    def test_view_i8_to_datetimelike(self):
+        dti = date_range("2000", periods=4, tz="US/Central")
+        ser = Series(dti.asi8)
+
+        result = ser.view(dti.dtype)
+        tm.assert_datetime_array_equal(result._values, dti._data._with_freq(None))
+
+        pi = dti.tz_localize(None).to_period("D")
+        ser = Series(pi.asi8)
+        result = ser.view(pi.dtype)
+        tm.assert_period_array_equal(result._values, pi._data)
+
     def test_view_tz(self):
         # GH#24024
         ser = Series(date_range("2000", periods=4, tz="US/Central"))