REGR: fix op(frame, frame2) with reindex

doc/source/whatsnew/v1.0.2.rst

@@ -19,6 +19,7 @@ Fixed regressions
 - Fixed regression in :meth:`Series.align` when ``other`` is a DataFrame and ``method`` is not None (:issue:`31785`)
 - Fixed regression in :meth:`pandas.core.groupby.RollingGroupby.apply` where the ``raw`` parameter was ignored (:issue:`31754`)
 - Fixed regression in :meth:`rolling(..).corr() <pandas.core.window.Rolling.corr>` when using a time offset (:issue:`31789`)
+- Fixed regression in :class:`DataFrame` arithmetic operations with mis-matched columns (:issue:`31623`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/ops/__init__.py

@@ -703,6 +703,56 @@ def to_series(right):
     return left, right
 
 
+def _should_reindex_frame_op(
+    left, right, axis, default_axis, fill_value, level
+) -> bool:
+    """
+    Check if this is an operation between DataFrames that will need to reindex.
+    """
+    assert isinstance(left, ABCDataFrame)
+
+    if not isinstance(right, ABCDataFrame):
+        return False
+
+    if fill_value is None and level is None and axis is default_axis:
+        # TODO: any other cases we should handle here?
+        cols = left.columns.intersection(right.columns)
+        if not (cols.equals(left.columns) and cols.equals(right.columns)):
+            return True
+
+    return False
+
+
+def _frame_arith_method_with_reindex(left, right, op):
+    """
+    For DataFrame-with-DataFrame operations that require reindexing,
+    operate only on shared columns, then reindex.
+
+    Parameters
+    ----------
+    left : DataFrame
+    right : DataFrame
+    op : binary operator
+
+    Returns
+    -------
+    DataFrame
+    """
+    # GH#31623, only operate on shared columns
+    cols = left.columns.intersection(right.columns)
+
+    new_left = left[cols]
+    new_right = right[cols]
+    result = op(new_left, new_right)
+
+    # Do the join on the columns instead of using _align_method_FRAME
+    #  to avoid constructing two potentially large/sparse DataFrames
+    join_columns, _, _ = left.columns.join(
+        right.columns, how="outer", level=None, return_indexers=True
+    )
+    return result.reindex(join_columns, axis=1)
+
+
 def _arith_method_FRAME(cls, op, special):
     str_rep = _get_opstr(op)
     op_name = _get_op_name(op, special)
@@ -720,6 +770,9 @@ def _arith_method_FRAME(cls, op, special):
     @Appender(doc)
     def f(self, other, axis=default_axis, level=None, fill_value=None):
 
+        if _should_reindex_frame_op(self, other, axis, default_axis, fill_value, level):
+            return _frame_arith_method_with_reindex(self, other, op)
+
         self, other = _align_method_FRAME(self, other, axis, flex=True, level=level)
 
         if isinstance(other, ABCDataFrame):

pandas/tests/frame/test_arithmetic.py

@@ -711,6 +711,25 @@ def test_operations_with_interval_categories_index(self, all_arithmetic_operator
         expected = pd.DataFrame([[getattr(n, op)(num) for n in data]], columns=ind)
         tm.assert_frame_equal(result, expected)
 
+    def test_frame_with_frame_reindex(self):
+        # GH#31623
+        df = pd.DataFrame(
+            {
+                "foo": [pd.Timestamp("2019"), pd.Timestamp("2020")],
+                "bar": [pd.Timestamp("2018"), pd.Timestamp("2021")],
+            },
+            columns=["foo", "bar"],
+        )
+        df2 = df[["foo"]]
+
+        result = df - df2
+
+        expected = pd.DataFrame(
+            {"foo": [pd.Timedelta(0), pd.Timedelta(0)], "bar": [np.nan, np.nan]},
+            columns=["bar", "foo"],
+        )
+        tm.assert_frame_equal(result, expected)
+
 
 def test_frame_with_zero_len_series_corner_cases():
     # GH#28600