WIP: Use dispatch_to_series for combine_const

pandas/core/frame.py

@@ -4867,10 +4867,34 @@ def _combine_const(self, other, func, errors='raise', try_cast=True):
         if lib.is_scalar(other) or np.ndim(other) == 0:
             return ops.dispatch_to_series(self, other, func)
 
-        new_data = self._data.eval(func=func, other=other,
-                                   errors=errors,
-                                   try_cast=try_cast)
-        return self._constructor(new_data)
+        elif (np.ndim(other) == 1 and isinstance(other, np.ndarray) and
+              len(other) == len(self.columns)):
+            right = np.broadcast_to(other, self.shape)
+            return ops.dispatch_to_series(self, right, func)
+
+        elif (np.ndim(other) == 1 and
+              isinstance(other, (tuple, np.ndarray)) and
+              len(other) == len(self) != len(self.columns)):
+            # tests include at least 1 tuple in this case
+            right = np.array(other)[:, None]
+            right = np.broadcast_to(right, self.shape)
+            return ops.dispatch_to_series(self, right, func)
+
+        elif np.ndim(other) == 1:
+            raise ValueError("Shape incompatible")
+
+        elif np.ndim(other) == 2 and other.shape == self.shape:
+            return ops.dispatch_to_series(self, other, func)
+
+        elif (np.ndim(other) == 2 and isinstance(other, np.ndarray) and
+              other.shape[0] == 1 and other.shape[1] == len(self.columns)):
+            other = np.broadcast_to(other, self.shape)
+            return ops.dispatch_to_series(self, other, func)
+
+        elif np.ndim(other) > 2:
+            raise ValueError("Wrong number of dimensions", other.shape)
+
+        raise ValueError(getattr(other, 'shape', type(other)))
 
     def combine(self, other, func, fill_value=None, overwrite=True):
         """

pandas/core/ops.py

@@ -1662,6 +1662,31 @@ def column_op(a, b):
             return {i: func(a.iloc[:, i], b)
                     for i in range(len(a.columns))}
 
+    elif np.ndim(right) == 2 and right.shape == left.shape:
+        # ndarray with same shape
+
+        def column_op(a, b):
+            return {i: func(a.iloc[:, i], b[:, i])
+                    for i in range(len(a.columns))}
+
+    elif (np.ndim(right) == 2 and
+          right.shape[0] == 1 and
+          right.shape[1] == len(left.columns)):
+        # operate row-by-row
+
+        def column_op(a, b):
+            return {i: func(a.iloc[:, i], b[0, i])
+                    for i in range(len(a.columns))}
+
+    elif (np.ndim(right) == 2 and
+          right.shape[1] == 1 and
+          right.shape[0] == len(left.index)):
+        # operate column-by-column
+
+        def column_op(a, b):
+            return {i: func(a.iloc[:, i], b[:, 0])
+                    for i in range(len(a.columns))}
+
     else:
         # Remaining cases have less-obvious dispatch rules
         raise NotImplementedError(right)