BUG: flex op with DataFrame, Series and ea vs ndarray

doc/source/whatsnew/v1.1.0.rst

@@ -686,6 +686,7 @@ Numeric
 - Bug in DataFrame reductions using ``numeric_only=True`` and ExtensionArrays (:issue:`33256`).
 - 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`)
+- Bug in :class:`DataFrame` flex arithmetic methods with ExtensionDtypes (:issue:`????`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/internals/blocks.py

@@ -332,11 +332,23 @@ def apply(self, func, **kwargs) -> List["Block"]:
         apply the function to my values; return a block if we are not
         one
         """
+        kwargs = self._ensure_same_shape_values(kwargs)
+
         with np.errstate(all="ignore"):
             result = func(self.values, **kwargs)
 
         return self._split_op_result(result)
 
+    def _ensure_same_shape_values(self, kwargs):
+        # TODO(EA2D): kludge for arithmetic not needed with 2D EA
+        if self.ndim == 2 and self.values.ndim == 1:
+            if "right" in kwargs and isinstance(kwargs["right"], np.ndarray):
+                right = kwargs["right"]
+                if right.ndim == 2:
+                    assert right.shape == (1, len(self.values)), right.shape
+                    kwargs["right"] = right[0]
+        return kwargs
+
     def _split_op_result(self, result) -> List["Block"]:
         # See also: split_and_operate
         if is_extension_array_dtype(result) and result.ndim > 1:

pandas/tests/frame/test_arithmetic.py

@@ -339,6 +339,20 @@ def test_df_flex_cmp_constant_return_types_empty(self, opname):
         result = getattr(empty, opname)(const).dtypes.value_counts()
         tm.assert_series_equal(result, pd.Series([2], index=[np.dtype(bool)]))
 
+    def test_df_flex_cmp_ea_dtype_with_ndarray_series(self):
+        ii = pd.IntervalIndex.from_breaks([1, 2, 3])
+        df = pd.DataFrame({"A": ii, "B": ii})
+
+        ser = pd.Series([0, 0])
+        res = df.eq(ser, axis=0)
+
+        expected = pd.DataFrame({"A": [False, False], "B": [False, False]})
+        tm.assert_frame_equal(res, expected)
+
+        ser2 = pd.Series([1, 2], index=["A", "B"])
+        res2 = df.eq(ser2, axis=1)
+        tm.assert_frame_equal(res2, expected)
+
 
 # -------------------------------------------------------------------
 # Arithmetic