DEPR: Series(dt64_naive, dtype=dt64tz) (#49242)

* DEPR: Series(dt64_naive, dtype=dt64tz)

* mypy fixup

Author: jbrockmendel

doc/source/whatsnew/v2.0.0.rst

@@ -165,6 +165,7 @@ Removal of prior version deprecations/changes
 - Removed deprecated :meth:`Index.is_mixed`, check ``index.inferred_type`` directly instead (:issue:`32922`)
 - Removed deprecated :func:`pandas.api.types.is_categorical`; use :func:`pandas.api.types.is_categorical_dtype` instead  (:issue:`33385`)
 - Removed deprecated :meth:`Index.asi8` (:issue:`37877`)
+- Enforced deprecation changing behavior when passing ``datetime64[ns]`` dtype data and timezone-aware dtype to :class:`Series`, interpreting the values as wall-times instead of UTC times, matching :class:`DatetimeIndex` behavior (:issue:`41662`)
 - Removed deprecated :meth:`DataFrame._AXIS_NUMBERS`, :meth:`DataFrame._AXIS_NAMES`, :meth:`Series._AXIS_NUMBERS`, :meth:`Series._AXIS_NAMES` (:issue:`33637`)
 - Removed deprecated :meth:`Index.to_native_types`, use ``obj.astype(str)`` instead (:issue:`36418`)
 - Removed deprecated :meth:`Series.iteritems`, :meth:`DataFrame.iteritems`, use ``obj.items`` instead (:issue:`45321`)

pandas/core/arrays/datetimes.py

@@ -2123,10 +2123,15 @@ def _sequence_to_dt64ns(
             # Convert tz-naive to UTC
             # TODO: if tz is UTC, are there situations where we *don't* want a
             #  copy?  tz_localize_to_utc always makes one.
+            shape = data.shape
+            if data.ndim > 1:
+                data = data.ravel()
+
             data = tzconversion.tz_localize_to_utc(
                 data.view("i8"), tz, ambiguous=ambiguous, creso=data_unit
             )
             data = data.view(new_dtype)
+            data = data.reshape(shape)
 
         assert data.dtype == new_dtype, data.dtype
         result = data

pandas/core/construction.py

@@ -55,10 +55,7 @@
     is_object_dtype,
     is_timedelta64_ns_dtype,
 )
-from pandas.core.dtypes.dtypes import (
-    DatetimeTZDtype,
-    PandasDtype,
-)
+from pandas.core.dtypes.dtypes import PandasDtype
 from pandas.core.dtypes.generic import (
     ABCExtensionArray,
     ABCIndex,
@@ -800,16 +797,6 @@ def _try_cast(
 
     elif isinstance(dtype, ExtensionDtype):
         # create an extension array from its dtype
-        if isinstance(dtype, DatetimeTZDtype):
-            # We can't go through _from_sequence because it handles dt64naive
-            #  data differently; _from_sequence treats naive as wall times,
-            #  while maybe_cast_to_datetime treats it as UTC
-            #  see test_maybe_promote_any_numpy_dtype_with_datetimetz
-            # TODO(2.0): with deprecations enforced, should be able to remove
-            #  special case.
-            return maybe_cast_to_datetime(arr, dtype)
-            # TODO: copy?
-
         array_type = dtype.construct_array_type()._from_sequence
         subarr = array_type(arr, dtype=dtype, copy=copy)
         return subarr

pandas/core/dtypes/cast.py

@@ -65,7 +65,6 @@
     is_complex,
     is_complex_dtype,
     is_datetime64_dtype,
-    is_datetime64tz_dtype,
     is_dtype_equal,
     is_extension_array_dtype,
     is_float,
@@ -1314,13 +1313,15 @@ def try_timedelta(v: np.ndarray) -> np.ndarray:
 
 
 def maybe_cast_to_datetime(
-    value: ExtensionArray | np.ndarray | list, dtype: DtypeObj | None
+    value: ExtensionArray | np.ndarray | list, dtype: np.dtype | None
 ) -> ExtensionArray | np.ndarray:
     """
     try to cast the array/value to a datetimelike dtype, converting float
     nan to iNaT
 
     We allow a list *only* when dtype is not None.
+
+    Caller is responsible for handling ExtensionDtype cases.
     """
     from pandas.core.arrays.datetimes import sequence_to_datetimes
     from pandas.core.arrays.timedeltas import TimedeltaArray
@@ -1332,18 +1333,22 @@ def maybe_cast_to_datetime(
         # TODO: _from_sequence would raise ValueError in cases where
         #  _ensure_nanosecond_dtype raises TypeError
         dtype = cast(np.dtype, dtype)
-        dtype = _ensure_nanosecond_dtype(dtype)
+        # Incompatible types in assignment (expression has type "Union[dtype[Any],
+        # ExtensionDtype]", variable has type "Optional[dtype[Any]]")
+        dtype = _ensure_nanosecond_dtype(dtype)  # type: ignore[assignment]
         res = TimedeltaArray._from_sequence(value, dtype=dtype)
         return res
 
     if dtype is not None:
         is_datetime64 = is_datetime64_dtype(dtype)
-        is_datetime64tz = is_datetime64tz_dtype(dtype)
 
         vdtype = getattr(value, "dtype", None)
 
-        if is_datetime64 or is_datetime64tz:
-            dtype = _ensure_nanosecond_dtype(dtype)
+        if is_datetime64:
+            # Incompatible types in assignment (expression has type
+            # "Union[dtype[Any], ExtensionDtype]", variable has type
+            # "Optional[dtype[Any]]")
+            dtype = _ensure_nanosecond_dtype(dtype)  # type: ignore[assignment]
 
             value = np.array(value, copy=False)
 
@@ -1352,59 +1357,22 @@ def maybe_cast_to_datetime(
                 _disallow_mismatched_datetimelike(value, dtype)
 
                 try:
-                    if is_datetime64:
-                        dta = sequence_to_datetimes(value)
-                        # GH 25843: Remove tz information since the dtype
-                        # didn't specify one
-
-                        if dta.tz is not None:
-                            raise ValueError(
-                                "Cannot convert timezone-aware data to "
-                                "timezone-naive dtype. Use "
-                                "pd.Series(values).dt.tz_localize(None) instead."
-                            )
-
-                        # TODO(2.0): Do this astype in sequence_to_datetimes to
-                        #  avoid potential extra copy?
-                        dta = dta.astype(dtype, copy=False)
-                        value = dta
-                    elif is_datetime64tz:
-                        dtype = cast(DatetimeTZDtype, dtype)
-                        # The string check can be removed once issue #13712
-                        # is solved. String data that is passed with a
-                        # datetime64tz is assumed to be naive which should
-                        # be localized to the timezone.
-                        is_dt_string = is_string_dtype(value.dtype)
-                        dta = sequence_to_datetimes(value)
-                        if dta.tz is not None:
-                            value = dta.astype(dtype, copy=False)
-                        elif is_dt_string:
-                            # Strings here are naive, so directly localize
-                            # equiv: dta.astype(dtype)  # though deprecated
-
-                            value = dta.tz_localize(dtype.tz)
-                        else:
-                            # Numeric values are UTC at this point,
-                            # so localize and convert
-                            # equiv: Series(dta).astype(dtype) # though deprecated
-                            if getattr(vdtype, "kind", None) == "M":
-                                # GH#24559, GH#33401 deprecate behavior inconsistent
-                                #  with DatetimeArray/DatetimeIndex
-                                warnings.warn(
-                                    "In a future version, constructing a Series "
-                                    "from datetime64[ns] data and a "
-                                    "DatetimeTZDtype will interpret the data "
-                                    "as wall-times instead of "
-                                    "UTC times, matching the behavior of "
-                                    "DatetimeIndex. To treat the data as UTC "
-                                    "times, use pd.Series(data).dt"
-                                    ".tz_localize('UTC').tz_convert(dtype.tz) "
-                                    "or pd.Series(data.view('int64'), dtype=dtype)",
-                                    FutureWarning,
-                                    stacklevel=find_stack_level(),
-                                )
-
-                            value = dta.tz_localize("UTC").tz_convert(dtype.tz)
+                    dta = sequence_to_datetimes(value)
+                    # GH 25843: Remove tz information since the dtype
+                    # didn't specify one
+
+                    if dta.tz is not None:
+                        raise ValueError(
+                            "Cannot convert timezone-aware data to "
+                            "timezone-naive dtype. Use "
+                            "pd.Series(values).dt.tz_localize(None) instead."
+                        )
+
+                    # TODO(2.0): Do this astype in sequence_to_datetimes to
+                    #  avoid potential extra copy?
+                    dta = dta.astype(dtype, copy=False)
+                    value = dta
+
                 except OutOfBoundsDatetime:
                     raise
                 except ParserError:

pandas/core/internals/construction.py

@@ -43,6 +43,7 @@
     is_named_tuple,
     is_object_dtype,
 )
+from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCSeries,
@@ -1054,7 +1055,15 @@ def _convert_object_array(
     def convert(arr):
         if dtype != np.dtype("O"):
             arr = lib.maybe_convert_objects(arr)
-            arr = maybe_cast_to_datetime(arr, dtype)
+
+            if isinstance(dtype, ExtensionDtype):
+                # TODO: test(s) that get here
+                # TODO: try to de-duplicate this convert function with
+                #  core.construction functions
+                cls = dtype.construct_array_type()
+                arr = cls._from_sequence(arr, dtype=dtype, copy=False)
+            else:
+                arr = maybe_cast_to_datetime(arr, dtype)
         return arr
 
     arrays = [convert(arr) for arr in content]

pandas/tests/series/test_constructors.py

@@ -1241,14 +1241,14 @@ def test_construction_consistency(self):
         result = Series(ser.dt.tz_convert("UTC"), dtype=ser.dtype)
         tm.assert_series_equal(result, ser)
 
-        msg = "will interpret the data as wall-times"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            # deprecate behavior inconsistent with DatetimeIndex GH#33401
-            result = Series(ser.values, dtype=ser.dtype)
-        tm.assert_series_equal(result, ser)
+        # Pre-2.0 dt64 values were treated as utc, which was inconsistent
+        #  with DatetimeIndex, which treats them as wall times, see GH#33401
+        result = Series(ser.values, dtype=ser.dtype)
+        expected = Series(ser.values).dt.tz_localize(ser.dtype.tz)
+        tm.assert_series_equal(result, expected)
 
         with tm.assert_produces_warning(None):
-            # one suggested alternative to the deprecated usage
+            # one suggested alternative to the deprecated (changed in 2.0) usage
             middle = Series(ser.values).dt.tz_localize("UTC")
             result = middle.dt.tz_convert(ser.dtype.tz)
         tm.assert_series_equal(result, ser)