Backport PR pandas-dev#38723: BUG: inconsistency between frame.any/al…

…l with dt64 vs dt64tz

doc/source/whatsnew/v1.2.1.rst

@@ -18,6 +18,8 @@ Fixed regressions
 - :meth:`to_csv` created corrupted zip files when there were more rows than ``chunksize`` (issue:`38714`)
 - Bug in repr of float-like strings of an ``object`` dtype having trailing 0's truncated after the decimal (:issue:`38708`)
 - Fixed regression in :meth:`DataFrame.groupby()` with :class:`Categorical` grouping column not showing unused categories for ``grouped.indices`` (:issue:`38642`)
+- Fixed regression in :meth:`DataFrame.any` and :meth:`DataFrame.all` not returning a result for tz-aware ``datetime64`` columns (:issue:`38723`)
+-
 
 .. ---------------------------------------------------------------------------
 

pandas/core/arrays/datetimelike.py

@@ -1621,6 +1621,17 @@ def floor(self, freq, ambiguous="raise", nonexistent="raise"):
     def ceil(self, freq, ambiguous="raise", nonexistent="raise"):
         return self._round(freq, RoundTo.PLUS_INFTY, ambiguous, nonexistent)
 
+    # --------------------------------------------------------------
+    # Reductions
+
+    def any(self, *, axis: Optional[int] = None, skipna: bool = True):
+        # GH#34479 discussion of desired behavior long-term
+        return nanops.nanany(self._ndarray, axis=axis, skipna=skipna, mask=self.isna())
+
+    def all(self, *, axis: Optional[int] = None, skipna: bool = True):
+        # GH#34479 discussion of desired behavior long-term
+        return nanops.nanall(self._ndarray, axis=axis, skipna=skipna, mask=self.isna())
+
     # --------------------------------------------------------------
     # Frequency Methods
 

pandas/tests/frame/test_reductions.py

@@ -1091,9 +1091,13 @@ def test_any_all_bool_only(self):
             (np.all, {"A": Series([0, 1], dtype=int)}, False),
             (np.any, {"A": Series([0, 1], dtype=int)}, True),
             pytest.param(np.all, {"A": Series([0, 1], dtype="M8[ns]")}, False),
+            pytest.param(np.all, {"A": Series([0, 1], dtype="M8[ns, UTC]")}, False),
             pytest.param(np.any, {"A": Series([0, 1], dtype="M8[ns]")}, True),
+            pytest.param(np.any, {"A": Series([0, 1], dtype="M8[ns, UTC]")}, True),
             pytest.param(np.all, {"A": Series([1, 2], dtype="M8[ns]")}, True),
+            pytest.param(np.all, {"A": Series([1, 2], dtype="M8[ns, UTC]")}, True),
             pytest.param(np.any, {"A": Series([1, 2], dtype="M8[ns]")}, True),
+            pytest.param(np.any, {"A": Series([1, 2], dtype="M8[ns, UTC]")}, True),
             pytest.param(np.all, {"A": Series([0, 1], dtype="m8[ns]")}, False),
             pytest.param(np.any, {"A": Series([0, 1], dtype="m8[ns]")}, True),
             pytest.param(np.all, {"A": Series([1, 2], dtype="m8[ns]")}, True),

pandas/tests/reductions/test_reductions.py

@@ -17,6 +17,7 @@
     Timedelta,
     TimedeltaIndex,
     Timestamp,
+    date_range,
     isna,
     timedelta_range,
     to_timedelta,
@@ -923,6 +924,48 @@ def test_any_axis1_bool_only(self):
         expected = Series([True, False])
         tm.assert_series_equal(result, expected)
 
+    def test_any_all_datetimelike(self):
+        # GH#38723 these may not be the desired long-term behavior (GH#34479)
+        #  but in the interim should be internally consistent
+        dta = date_range("1995-01-02", periods=3)._data
+        ser = Series(dta)
+        df = DataFrame(ser)
+
+        assert dta.all()
+        assert dta.any()
+
+        assert ser.all()
+        assert ser.any()
+
+        assert df.any().all()
+        assert df.all().all()
+
+        dta = dta.tz_localize("UTC")
+        ser = Series(dta)
+        df = DataFrame(ser)
+
+        assert dta.all()
+        assert dta.any()
+
+        assert ser.all()
+        assert ser.any()
+
+        assert df.any().all()
+        assert df.all().all()
+
+        tda = dta - dta[0]
+        ser = Series(tda)
+        df = DataFrame(ser)
+
+        assert tda.any()
+        assert not tda.all()
+
+        assert ser.any()
+        assert not ser.all()
+
+        assert df.any().all()
+        assert not df.all().any()
+
     def test_timedelta64_analytics(self):
 
         # index min/max