Use dispatch_to_series where possible (pandas-dev#22572)

Author: jbrockmendel

pandas/core/frame.py

@@ -4818,13 +4818,14 @@ def _arith_op(left, right):
             return ops.dispatch_to_series(this, other, _arith_op)
         else:
             result = _arith_op(this.values, other.values)
-
-        return self._constructor(result, index=new_index, columns=new_columns,
-                                 copy=False)
+            return self._constructor(result,
+                                     index=new_index, columns=new_columns,
+                                     copy=False)
 
     def _combine_match_index(self, other, func, level=None):
         left, right = self.align(other, join='outer', axis=0, level=level,
                                  copy=False)
+        assert left.index.equals(right.index)
         new_data = func(left.values.T, right.values).T
         return self._constructor(new_data,
                                  index=left.index, columns=self.columns,
@@ -4833,6 +4834,7 @@ def _combine_match_index(self, other, func, level=None):
     def _combine_match_columns(self, other, func, level=None, try_cast=True):
         left, right = self.align(other, join='outer', axis=1, level=level,
                                  copy=False)
+        assert left.columns.equals(right.index)
 
         new_data = left._data.eval(func=func, other=right,
                                    axes=[left.columns, self.index],
@@ -4841,12 +4843,7 @@ def _combine_match_columns(self, other, func, level=None, try_cast=True):
 
     def _combine_const(self, other, func, errors='raise', try_cast=True):
         if lib.is_scalar(other) or np.ndim(other) == 0:
-            new_data = {i: func(self.iloc[:, i], other)
-                        for i, col in enumerate(self.columns)}
-
-            result = self._constructor(new_data, index=self.index, copy=False)
-            result.columns = self.columns
-            return result
+            return ops.dispatch_to_series(self, other, func)
 
         new_data = self._data.eval(func=func, other=other,
                                    errors=errors,

pandas/core/ops.py

@@ -1638,6 +1638,7 @@ def dispatch_to_series(left, right, func):
     """
     # Note: we use iloc to access columns for compat with cases
     #       with non-unique columns.
+    right = lib.item_from_zerodim(right)
     if lib.is_scalar(right):
         new_data = {i: func(left.iloc[:, i], right)
                     for i in range(len(left.columns))}