Series.values deprecation of converts and drops

doc/source/whatsnew/v3.0.0.rst

@@ -200,6 +200,7 @@ starting with 3.0, so it can be safely removed from your code.
 Other Deprecations
 ^^^^^^^^^^^^^^^^^^
 
+- Deprecated :meth:`series.values`, now don't drops the ``tz`` from ``dt64tz``, converts ``interval`` to ``object``, converts ``period`` to ``object``.
 - Deprecated :meth:`Timestamp.utcfromtimestamp`, use ``Timestamp.fromtimestamp(ts, "UTC")`` instead (:issue:`56680`)
 - Deprecated :meth:`Timestamp.utcnow`, use ``Timestamp.now("UTC")`` instead (:issue:`56680`)
 - Deprecated allowing non-keyword arguments in :meth:`DataFrame.all`, :meth:`DataFrame.min`, :meth:`DataFrame.max`, :meth:`DataFrame.sum`, :meth:`DataFrame.prod`, :meth:`DataFrame.mean`, :meth:`DataFrame.median`, :meth:`DataFrame.sem`, :meth:`DataFrame.var`, :meth:`DataFrame.std`, :meth:`DataFrame.skew`, :meth:`DataFrame.kurt`, :meth:`Series.all`,  :meth:`Series.min`, :meth:`Series.max`, :meth:`Series.sum`, :meth:`Series.prod`, :meth:`Series.mean`, :meth:`Series.median`, :meth:`Series.sem`, :meth:`Series.var`, :meth:`Series.std`, :meth:`Series.skew`, and :meth:`Series.kurt`. (:issue:`57087`)

pandas/core/internals/blocks.py

@@ -2349,11 +2349,21 @@ def external_values(values: ArrayLike) -> ArrayLike:
     proper extension array).
     """
     if isinstance(values, (PeriodArray, IntervalArray)):
+        warnings.warn(
+            "series.values will stop converting tz from dt64tz, interval to object and period to object",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
         return values.astype(object)
     elif isinstance(values, (DatetimeArray, TimedeltaArray)):
         # NB: for datetime64tz this is different from np.asarray(values), since
         #  that returns an object-dtype ndarray of Timestamps.
         # Avoid raising in .astype in casting from dt64tz to dt64
+        warnings.warn(
+            "series.values will stop converting tz from dt64tz, interval to object and period to object",
+            FutureWarning,
+            stacklevel=find_stack_level(),
+        )
         values = values._ndarray
 
     if isinstance(values, np.ndarray):

pandas/tests/arithmetic/test_datetime64.py

@@ -2329,9 +2329,17 @@ def test_dti_add_series(self, tz_naive_fixture, names):
         tm.assert_series_equal(result2, expected)
 
         expected = index + Timedelta(seconds=5)
-        result3 = ser.values + index
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            result3 = ser.values + index
         tm.assert_index_equal(result3, expected)
-        result4 = index + ser.values
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            result4 = index + ser.values
         tm.assert_index_equal(result4, expected)
 
     @pytest.mark.parametrize("op", [operator.add, roperator.radd, operator.sub])

pandas/tests/arrays/test_timedeltas.py

@@ -74,7 +74,11 @@ def test_total_seconds_nanoseconds(self):
         # issue #48521
         start_time = pd.Series(["2145-11-02 06:00:00"]).astype("datetime64[ns]")
         end_time = pd.Series(["2145-11-02 07:06:00"]).astype("datetime64[ns]")
-        expected = (end_time - start_time).values / np.timedelta64(1, "s")
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            expected = (end_time - start_time).values / np.timedelta64(1, "s")
         result = (end_time - start_time).dt.total_seconds().values
         assert result == expected
 

pandas/tests/base/test_value_counts.py

@@ -254,7 +254,11 @@ def test_value_counts_datetime64(index_or_series, unit):
 
     # with NaT
     s = df["dt"].copy()
-    s = klass(list(s.values) + [pd.NaT] * 4)
+    with tm.assert_produces_warning(
+        FutureWarning,
+        match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+    ):
+        s = klass(list(s.values) + [pd.NaT] * 4)
     if klass is Series:
         s = s.dt.as_unit(unit)
     else:

pandas/tests/computation/test_eval.py

@@ -1507,12 +1507,16 @@ def test_nested_period_index_subscript_expression(self):
     def test_date_boolean(self, engine, parser):
         df = DataFrame(np.random.default_rng(2).standard_normal((5, 3)))
         df["dates1"] = date_range("1/1/2012", periods=5)
-        res = self.eval(
-            "df.dates1 < 20130101",
-            local_dict={"df": df},
-            engine=engine,
-            parser=parser,
-        )
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            res = self.eval(
+                "df.dates1 < 20130101",
+                local_dict={"df": df},
+                engine=engine,
+                parser=parser,
+            )
         expec = df.dates1 < "20130101"
         tm.assert_series_equal(res, expec)
 

pandas/tests/copy_view/test_astype.py

@@ -187,7 +187,11 @@ def test_astype_arrow_timestamp():
         },
         dtype="M8[ns]",
     )
-    result = df.astype("timestamp[ns][pyarrow]")
+    with tm.assert_produces_warning(
+        FutureWarning,
+        match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+    ):
+        result = df.astype("timestamp[ns][pyarrow]")
     assert not result._mgr._has_no_reference(0)
     if pa_version_under12p0:
         assert not np.shares_memory(

pandas/tests/frame/indexing/test_setitem.py

@@ -305,7 +305,11 @@ def test_frame_setitem_datetime64_col_other_units(self, unit):
         df[unit] = vals
 
         assert df[unit].dtype == ex_vals.dtype
-        assert (df[unit].values == ex_vals).all()
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            assert (df[unit].values == ex_vals).all()
 
     @pytest.mark.parametrize("unit", ["h", "m", "s", "ms", "D", "M", "Y"])
     def test_frame_setitem_existing_datetime64_col_other_units(self, unit):
@@ -322,7 +326,11 @@ def test_frame_setitem_existing_datetime64_col_other_units(self, unit):
 
         # We overwrite existing dt64 column with new, non-nano dt64 vals
         df["dates"] = vals
-        assert (df["dates"].values == ex_vals).all()
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            assert (df["dates"].values == ex_vals).all()
 
     def test_setitem_dt64tz(self, timezone_frame):
         df = timezone_frame

pandas/tests/frame/methods/test_convert_dtypes.py

@@ -61,7 +61,11 @@ def test_pyarrow_dtype_backend(self):
                 "g": pd.Series(pd.timedelta_range("1D", periods=3)),
             }
         )
-        result = df.convert_dtypes(dtype_backend="pyarrow")
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            result = df.convert_dtypes(dtype_backend="pyarrow")
         expected = pd.DataFrame(
             {
                 "a": pd.arrays.ArrowExtensionArray(
@@ -176,7 +180,11 @@ def test_convert_dtypes_pyarrow_timestamp(self):
         # GH 54191
         pytest.importorskip("pyarrow")
         ser = pd.Series(pd.date_range("2020-01-01", "2020-01-02", freq="1min"))
-        expected = ser.astype("timestamp[ms][pyarrow]")
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            expected = ser.astype("timestamp[ms][pyarrow]")
         result = expected.convert_dtypes(dtype_backend="pyarrow")
         tm.assert_series_equal(result, expected)
 

pandas/tests/frame/methods/test_duplicated.py

@@ -109,7 +109,11 @@ def test_frame_datetime64_duplicated():
     dates = date_range("2010-07-01", end="2010-08-05")
 
     tst = DataFrame({"symbol": "AAA", "date": dates})
-    result = tst.duplicated(["date", "symbol"])
+    with tm.assert_produces_warning(
+        FutureWarning,
+        match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+    ):
+        result = tst.duplicated(["date", "symbol"])
     assert (-result).all()
 
     tst = DataFrame({"date": dates})

pandas/tests/frame/test_block_internals.py

@@ -293,13 +293,21 @@ def test_consolidate_datetime64(self):
         )
 
         ser_starting = df.starting
-        ser_starting.index = ser_starting.values
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            ser_starting.index = ser_starting.values
         ser_starting = ser_starting.tz_localize("US/Eastern")
         ser_starting = ser_starting.tz_convert("UTC")
         ser_starting.index.name = "starting"
 
         ser_ending = df.ending
-        ser_ending.index = ser_ending.values
+        with tm.assert_produces_warning(
+            FutureWarning,
+            match="series.values will stop converting tz from dt64tz, interval to object and period to object",
+        ):
+            ser_ending.index = ser_ending.values
         ser_ending = ser_ending.tz_localize("US/Eastern")
         ser_ending = ser_ending.tz_convert("UTC")
         ser_ending.index.name = "ending"