Requested Follow-Ups (pandas-dev#33856)

Author: jbrockmendel

doc/source/whatsnew/v1.1.0.rst

@@ -544,6 +544,7 @@ Datetimelike
 - Bug in :meth:`DatetimeIndex.tz_localize` incorrectly retaining ``freq`` in some cases where the original freq is no longer valid (:issue:`30511`)
 - Bug in :meth:`DatetimeIndex.intersection` losing ``freq`` and timezone in some cases (:issue:`33604`)
 - Bug in :class:`DatetimeIndex` addition and subtraction with some types of :class:`DateOffset` objects incorrectly retaining an invalid ``freq`` attribute (:issue:`33779`)
+- Bug in :class:`DatetimeIndex` where setting the ``freq`` attribute on an index could silently change the ``freq`` attribute on another index viewing the same data (:issue:`33552`)
 
 Timedelta
 ^^^^^^^^^
@@ -570,6 +571,7 @@ Numeric
 - Bug in :meth:`DataFrame.count` with ``level="foo"`` and index level ``"foo"`` containing NaNs causes segmentation fault (:issue:`21824`)
 - Bug in :meth:`DataFrame.diff` with ``axis=1`` returning incorrect results with mixed dtypes (:issue:`32995`)
 - Bug in :meth:`DataFrame.corr` and :meth:`DataFrame.cov` raising when handling nullable integer columns with ``pandas.NA`` (:issue:`33803`)
+- Bug in :class:`DataFrame` and :class:`Series` addition and subtraction between object-dtype objects and ``datetime64`` dtype objects (:issue:`33824`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/array_algos/transforms.py

@@ -10,9 +10,8 @@
 def shift(values: np.ndarray, periods: int, axis: int, fill_value) -> np.ndarray:
     new_values = values
 
-    if periods == 0:
-        # TODO: should we copy here?
-        return new_values
+    if periods == 0 or values.size == 0:
+        return new_values.copy()
 
     # make sure array sent to np.roll is c_contiguous
     f_ordered = values.flags.f_contiguous

pandas/core/arrays/categorical.py

@@ -1196,7 +1196,7 @@ def shift(self, periods, fill_value=None):
 
         fill_value = self._validate_fill_value(fill_value)
 
-        codes = shift(codes.copy(), periods, axis=0, fill_value=fill_value)
+        codes = shift(codes, periods, axis=0, fill_value=fill_value)
 
         return self._constructor(codes, dtype=self.dtype, fastpath=True)
 

pandas/core/arrays/datetimelike.py

@@ -699,8 +699,6 @@ def _values_for_argsort(self):
 
     @Appender(ExtensionArray.shift.__doc__)
     def shift(self, periods=1, fill_value=None, axis=0):
-        if not self.size or periods == 0:
-            return self.copy()
 
         fill_value = self._validate_shift_value(fill_value)
         new_values = shift(self._data, periods, axis, fill_value)
@@ -745,7 +743,9 @@ def _validate_shift_value(self, fill_value):
         # TODO(2.0): once this deprecation is enforced, used _validate_fill_value
         if is_valid_nat_for_dtype(fill_value, self.dtype):
             fill_value = NaT
-        elif not isinstance(fill_value, self._recognized_scalars):
+        elif isinstance(fill_value, self._recognized_scalars):
+            fill_value = self._scalar_type(fill_value)
+        else:
             # only warn if we're not going to raise
             if self._scalar_type is Period and lib.is_integer(fill_value):
                 # kludge for #31971 since Period(integer) tries to cast to str

pandas/core/internals/blocks.py

@@ -2237,7 +2237,12 @@ def diff(self, n: int, axis: int = 0) -> List["Block"]:
             # Cannot currently calculate diff across multiple blocks since this
             # function is invoked via apply
             raise NotImplementedError
-        new_values = (self.values - self.shift(n, axis=axis)[0].values).asi8
+
+        if n == 0:
+            # Fastpath avoids making a copy in `shift`
+            new_values = np.zeros(self.values.shape, dtype=np.int64)
+        else:
+            new_values = (self.values - self.shift(n, axis=axis)[0].values).asi8
 
         # Reshape the new_values like how algos.diff does for timedelta data
         new_values = new_values.reshape(1, len(new_values))

pandas/tests/arrays/test_datetimes.py

@@ -374,6 +374,40 @@ def test_searchsorted_invalid_types(self, other, index):
         with pytest.raises(TypeError, match=msg):
             arr.searchsorted(other)
 
+    def test_shift_fill_value(self):
+        dti = pd.date_range("2016-01-01", periods=3)
+
+        dta = dti._data
+        expected = DatetimeArray(np.roll(dta._data, 1))
+
+        fv = dta[-1]
+        for fill_value in [fv, fv.to_pydatetime(), fv.to_datetime64()]:
+            result = dta.shift(1, fill_value=fill_value)
+            tm.assert_datetime_array_equal(result, expected)
+
+        dta = dta.tz_localize("UTC")
+        expected = expected.tz_localize("UTC")
+        fv = dta[-1]
+        for fill_value in [fv, fv.to_pydatetime()]:
+            result = dta.shift(1, fill_value=fill_value)
+            tm.assert_datetime_array_equal(result, expected)
+
+    def test_shift_value_tzawareness_mismatch(self):
+        dti = pd.date_range("2016-01-01", periods=3)
+
+        dta = dti._data
+
+        fv = dta[-1].tz_localize("UTC")
+        for invalid in [fv, fv.to_pydatetime()]:
+            with pytest.raises(TypeError, match="Cannot compare"):
+                dta.shift(1, fill_value=invalid)
+
+        dta = dta.tz_localize("UTC")
+        fv = dta[-1].tz_localize(None)
+        for invalid in [fv, fv.to_pydatetime(), fv.to_datetime64()]:
+            with pytest.raises(TypeError, match="Cannot compare"):
+                dta.shift(1, fill_value=invalid)
+
 
 class TestSequenceToDT64NS:
     def test_tz_dtype_mismatch_raises(self):

pandas/tests/extension/base/methods.py

@@ -237,6 +237,13 @@ def test_container_shift(self, data, frame, periods, indices):
 
         compare(result, expected)
 
+    def test_shift_0_periods(self, data):
+        # GH#33856 shifting with periods=0 should return a copy, not same obj
+        result = data.shift(0)
+        assert data[0] != data[1]  # otherwise below is invalid
+        data[0] = data[1]
+        assert result[0] != result[1]  # i.e. not the same object/view
+
     @pytest.mark.parametrize("periods", [1, -2])
     def test_diff(self, data, periods):
         data = data[:5]

pandas/tests/extension/test_sparse.py

@@ -309,6 +309,13 @@ def test_searchsorted(self, data_for_sorting, as_series):
         with tm.assert_produces_warning(PerformanceWarning):
             super().test_searchsorted(data_for_sorting, as_series)
 
+    def test_shift_0_periods(self, data):
+        # GH#33856 shifting with periods=0 should return a copy, not same obj
+        result = data.shift(0)
+
+        data._sparse_values[0] = data._sparse_values[1]
+        assert result._sparse_values[0] != result._sparse_values[1]
+
 
 class TestCasting(BaseSparseTests, base.BaseCastingTests):
     def test_astype_object_series(self, all_data):