BUG: DTA/TDA/PA/Series/Index.view with datetimelike

doc/source/whatsnew/v1.3.0.rst

@@ -312,7 +312,7 @@ Numeric
 
 Conversion
 ^^^^^^^^^^
--
+- Bug in :meth:`Series.view` and :meth:`Index.view` when converting between datetime-like (``datetime64[ns]``, ``datetime64[ns, tz]``, ``timedelta64``, ``period``) dtypes (:issue:`39788`)
 -
 
 Strings

pandas/core/arrays/datetimelike.py

@@ -34,7 +34,7 @@
 )
 from pandas._libs.tslibs.fields import RoundTo, round_nsint64
 from pandas._libs.tslibs.timestamps import integer_op_not_supported
-from pandas._typing import DatetimeLikeScalar, Dtype, DtypeObj, NpDtype
+from pandas._typing import ArrayLike, DatetimeLikeScalar, Dtype, DtypeObj, NpDtype
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError, NullFrequencyError, PerformanceWarning
 from pandas.util._decorators import Appender, Substitution, cache_readonly
@@ -57,6 +57,7 @@
     is_unsigned_integer_dtype,
     pandas_dtype,
 )
+from pandas.core.dtypes.dtypes import DatetimeTZDtype, PeriodDtype
 from pandas.core.dtypes.missing import is_valid_na_for_dtype, isna
 
 from pandas.core import nanops, ops
@@ -381,9 +382,26 @@ def astype(self, dtype, copy=True):
         else:
             return np.asarray(self, dtype=dtype)
 
-    def view(self, dtype: Optional[Dtype] = None):
+    def view(self, dtype: Optional[Dtype] = None) -> ArrayLike:
         if dtype is None or dtype is self.dtype:
             return type(self)(self._ndarray, dtype=self.dtype)
+
+        if isinstance(dtype, type):
+            # e.g. np.ndarray
+            return self._ndarray.view(dtype)
+
+        dtype = pandas_dtype(dtype)
+        if isinstance(dtype, (PeriodDtype, DatetimeTZDtype)):
+            cls = dtype.construct_array_type()
+            return cls._simple_new(self.asi8, dtype=dtype)
+        elif dtype == "M8[ns]":
+            from pandas.core.arrays import DatetimeArray
+
+            return DatetimeArray._simple_new(self.asi8, dtype=dtype)
+        elif dtype == "m8[ns]":
+            from pandas.core.arrays import TimedeltaArray
+
+            return TimedeltaArray._simple_new(self.asi8.view("m8[ns]"), dtype=dtype)
         return self._ndarray.view(dtype=dtype)
 
     # ------------------------------------------------------------------

pandas/core/indexes/base.py

@@ -747,6 +747,23 @@ def view(self, cls=None):
         # we need to see if we are subclassing an
         # index type here
         if cls is not None and not hasattr(cls, "_typ"):
+            dtype = cls
+            if isinstance(cls, str):
+                dtype = pandas_dtype(cls)
+
+            if isinstance(dtype, (np.dtype, ExtensionDtype)) and needs_i8_conversion(
+                dtype
+            ):
+                if dtype.kind == "m" and dtype != "m8[ns]":
+                    # 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._simple_new(self._data.view("i8"), dtype=dtype)
+                return idx_cls._simple_new(arr, name=self.name)
+
             result = self._data.view(cls)
         else:
             result = self._view()

pandas/tests/series/methods/test_view.py

@@ -1,4 +1,7 @@
-from pandas import Series, date_range
+import numpy as np
+import pytest
+
+from pandas import Index, Series, array as pd_array, date_range
 import pandas._testing as tm
 
 
@@ -16,3 +19,23 @@ def test_view_tz(self):
             ]
         )
         tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "first", ["m8[ns]", "M8[ns]", "M8[ns, US/Central]", "period[D]"]
+    )
+    @pytest.mark.parametrize(
+        "second", ["m8[ns]", "M8[ns]", "M8[ns, US/Central]", "period[D]"]
+    )
+    @pytest.mark.parametrize("box", [Series, Index, pd_array])
+    def test_view_between_datetimelike(self, first, second, box):
+
+        dti = date_range("2016-01-01", periods=3)
+
+        orig = box(dti)
+        obj = orig.view(first)
+        assert obj.dtype == first
+        tm.assert_numpy_array_equal(np.asarray(obj.view("i8")), dti.asi8)
+
+        res = obj.view(second)
+        assert res.dtype == second
+        tm.assert_numpy_array_equal(np.asarray(obj.view("i8")), dti.asi8)