DEPR: passing td64 data to DTA or dt64 data to TDA (pandas-dev#29794)

doc/source/whatsnew/v1.0.0.rst

@@ -407,6 +407,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 - Removed the previously deprecated :meth:`Series.get_value`, :meth:`Series.set_value`, :meth:`DataFrame.get_value`, :meth:`DataFrame.set_value` (:issue:`17739`)
 - Changed the the default value of `inplace` in :meth:`DataFrame.set_index` and :meth:`Series.set_axis`. It now defaults to False (:issue:`27600`)
 - Removed support for nested renaming in :meth:`DataFrame.aggregate`, :meth:`Series.aggregate`, :meth:`DataFrameGroupBy.aggregate`, :meth:`SeriesGroupBy.aggregate`, :meth:`Rolling.aggregate` (:issue:`18529`)
+- Passing ``datetime64`` data to :class:`TimedeltaIndex` or ``timedelta64`` data to ``DatetimeIndex`` now raises ``TypeError`` (:issue:`23539`, :issue:`23937`)
 - A tuple passed to :meth:`DataFrame.groupby` is now exclusively treated as a single key (:issue:`18314`)
 - Removed :meth:`Series.from_array` (:issue:`18258`)
 - Removed :meth:`DataFrame.from_items` (:issue:`18458`)

pandas/core/arrays/datetimes.py

@@ -2102,14 +2102,8 @@ def maybe_convert_dtype(data, copy):
         #  with integer dtypes.  See discussion in GH#23675
 
     elif is_timedelta64_dtype(data):
-        warnings.warn(
-            "Passing timedelta64-dtype data is deprecated, will "
-            "raise a TypeError in a future version",
-            FutureWarning,
-            stacklevel=5,
-        )
-        data = data.view(_NS_DTYPE)
-
+        # GH#29794 enforcing deprecation introduced in GH#23539
+        raise TypeError(f"dtype {data.dtype} cannot be converted to datetime64[ns]")
     elif is_period_dtype(data):
         # Note: without explicitly raising here, PeriodIndex
         #  test_setops.test_join_does_not_recur fails

pandas/core/arrays/timedeltas.py

@@ -20,8 +20,6 @@
 from pandas.core.dtypes.common import (
     _NS_DTYPE,
     _TD_DTYPE,
-    ensure_int64,
-    is_datetime64_dtype,
     is_dtype_equal,
     is_float_dtype,
     is_integer_dtype,
@@ -1056,18 +1054,8 @@ def sequence_to_td64ns(data, copy=False, unit="ns", errors="raise"):
             data = data.astype(_TD_DTYPE)
             copy = False
 
-    elif is_datetime64_dtype(data):
-        # GH#23539
-        warnings.warn(
-            "Passing datetime64-dtype data to TimedeltaIndex is "
-            "deprecated, will raise a TypeError in a future "
-            "version",
-            FutureWarning,
-            stacklevel=4,
-        )
-        data = ensure_int64(data).view(_TD_DTYPE)
-
     else:
+        # This includes datetime64-dtype, see GH#23539, GH#29794
         raise TypeError(
             "dtype {dtype} cannot be converted to timedelta64[ns]".format(
                 dtype=data.dtype

pandas/tests/arithmetic/test_timedelta64.py

@@ -577,15 +577,23 @@ def test_timedelta_ops_with_missing_values(self):
         # setup
         s1 = pd.to_timedelta(Series(["00:00:01"]))
         s2 = pd.to_timedelta(Series(["00:00:02"]))
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            # Passing datetime64-dtype data to TimedeltaIndex is deprecated
-            sn = pd.to_timedelta(Series([pd.NaT]))
+
+        msg = r"dtype datetime64\[ns\] cannot be converted to timedelta64\[ns\]"
+        with pytest.raises(TypeError, match=msg):
+            # Passing datetime64-dtype data to TimedeltaIndex is no longer
+            #  supported GH#29794
+            pd.to_timedelta(Series([pd.NaT]))
+
+        sn = pd.to_timedelta(Series([pd.NaT], dtype="m8[ns]"))
 
         df1 = pd.DataFrame(["00:00:01"]).apply(pd.to_timedelta)
         df2 = pd.DataFrame(["00:00:02"]).apply(pd.to_timedelta)
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            # Passing datetime64-dtype data to TimedeltaIndex is deprecated
-            dfn = pd.DataFrame([pd.NaT]).apply(pd.to_timedelta)
+        with pytest.raises(TypeError, match=msg):
+            # Passing datetime64-dtype data to TimedeltaIndex is no longer
+            #  supported GH#29794
+            pd.DataFrame([pd.NaT]).apply(pd.to_timedelta)
+
+        dfn = pd.DataFrame([pd.NaT.value]).apply(pd.to_timedelta)
 
         scalar1 = pd.to_timedelta("00:00:01")
         scalar2 = pd.to_timedelta("00:00:02")

pandas/tests/indexes/datetimes/test_construction.py

@@ -70,28 +70,21 @@ def test_dti_with_period_data_raises(self):
         with pytest.raises(TypeError, match="PeriodDtype data is invalid"):
             to_datetime(period_array(data))
 
-    def test_dti_with_timedelta64_data_deprecation(self):
-        # GH#23675
+    def test_dti_with_timedelta64_data_raises(self):
+        # GH#23675 deprecated, enforrced in GH#29794
         data = np.array([0], dtype="m8[ns]")
-        with tm.assert_produces_warning(FutureWarning):
-            result = DatetimeIndex(data)
-
-        assert result[0] == Timestamp("1970-01-01")
-
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            result = to_datetime(data)
-
-        assert result[0] == Timestamp("1970-01-01")
-
-        with tm.assert_produces_warning(FutureWarning):
-            result = DatetimeIndex(pd.TimedeltaIndex(data))
+        msg = r"timedelta64\[ns\] cannot be converted to datetime64"
+        with pytest.raises(TypeError, match=msg):
+            DatetimeIndex(data)
 
-        assert result[0] == Timestamp("1970-01-01")
+        with pytest.raises(TypeError, match=msg):
+            to_datetime(data)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            result = to_datetime(pd.TimedeltaIndex(data))
+        with pytest.raises(TypeError, match=msg):
+            DatetimeIndex(pd.TimedeltaIndex(data))
 
-        assert result[0] == Timestamp("1970-01-01")
+        with pytest.raises(TypeError, match=msg):
+            to_datetime(pd.TimedeltaIndex(data))
 
     def test_construction_caching(self):
 

pandas/tests/indexes/timedeltas/test_construction.py

@@ -60,17 +60,17 @@ def test_infer_from_tdi_mismatch(self):
     def test_dt64_data_invalid(self):
         # GH#23539
         # passing tz-aware DatetimeIndex raises, naive or ndarray[datetime64]
-        #  does not yet, but will in the future
+        #  raise as of GH#29794
         dti = pd.date_range("2016-01-01", periods=3)
 
         msg = "cannot be converted to timedelta64"
         with pytest.raises(TypeError, match=msg):
             TimedeltaIndex(dti.tz_localize("Europe/Brussels"))
 
-        with tm.assert_produces_warning(FutureWarning):
+        with pytest.raises(TypeError, match=msg):
             TimedeltaIndex(dti)
 
-        with tm.assert_produces_warning(FutureWarning):
+        with pytest.raises(TypeError, match=msg):
             TimedeltaIndex(np.asarray(dti))
 
     def test_float64_ns_rounded(self):