No inplace, but with duplication of input data

Author: Nick Eubank

pandas/tools/merge.py

@@ -186,8 +186,7 @@ def __init__(self, left, right, how='inner', on=None,
 
     def get_result(self):
         if self.indicator:
-            # Has side-effects. Most cleaned up in `self._indicator_post_merge`          
-            self._indicator_pre_merge(self.left, self.right)
+            self.left, self.right = self._indicator_pre_merge(self.left, self.right)
 
         join_index, left_indexer, right_indexer = self._get_join_info()
 
@@ -209,8 +208,7 @@ def get_result(self):
         result = typ(result_data).__finalize__(self, method='merge')
 
         if self.indicator:
-            # Has side-effects
-            self._indicator_post_merge(result, self.left, self.right)
+            result = self._indicator_post_merge(result)
 
         self._maybe_add_join_keys(result, left_indexer, right_indexer)
 
@@ -224,24 +222,28 @@ def _indicator_pre_merge(self, left, right):
             if i in columns:
                 raise ValueError("Cannot use `indicator=True` option when data contains a column named {}".format(i))
 
+        left = left.copy()
+        right = right.copy()
+
         left['_left_indicator'] = 1  
         left['_left_indicator'] = left['_left_indicator'].astype('int8')  
 
         right['_right_indicator'] = 2     
-        right['_right_indicator'] = right['_right_indicator'].astype('int8')  
+        right['_right_indicator'] = right['_right_indicator'].astype('int8') 
+        
+        return left, right
 
+    def _indicator_post_merge(self, result):
+
+        result['_left_indicator'] = result['_left_indicator'].fillna(0)
+        result['_right_indicator'] = result['_right_indicator'].fillna(0)
 
-    def _indicator_post_merge(self, result, left, right):
-        result['_left_indicator'].fillna(0, inplace=True)        
-        result['_right_indicator'].fillna(0, inplace=True)
-        
         result['_merge'] = Categorical((result['_left_indicator'] + result['_right_indicator']), categories=[1,2,3])
-        result['_merge'].cat.rename_categories(['left_only', 'right_only', 'both'], inplace=True)        
+        result['_merge'] = result['_merge'].cat.rename_categories(['left_only', 'right_only', 'both'])        
 
-       # Cleanup
-        result.drop(labels=['_left_indicator', '_right_indicator'], axis=1, inplace=True)
-        left.drop(labels=['_left_indicator'], axis=1, inplace=True)
-        right.drop(labels=['_right_indicator'], axis=1, inplace=True)
+        result = result.drop(labels=['_left_indicator', '_right_indicator'], axis=1)
+
+        return result
 
     def _maybe_add_join_keys(self, result, left_indexer, right_indexer):
         # insert group keys

pandas/tools/tests/test_merge.py

@@ -858,23 +858,30 @@ def test_overlapping_columns_error_message(self):
 
     def test_indicator(self):
 
-        df1 = pd.DataFrame({'col1':[0,1], 'col_left':['a','b']})
+        df1 = pd.DataFrame({'col1':[0,1], 'col_left':['a','b'], 'col_conflict':[1,2]})
         df1_copy = df1.copy()
 
-        df2 = pd.DataFrame({'col1':[1,2,3,4,5],'col_right':[2,2,2,2,2]})
+        df2 = pd.DataFrame({'col1':[1,2,3,4,5],'col_right':[2,2,2,2,2], 
+                            'col_conflict':[1,2,3,4,5]})
         df2_copy = df2.copy()
 
         df_result = pd.DataFrame({'col1':[0,1,2,3,4,5], 
+                'col_conflict_x':[1,2,np.nan,np.nan,np.nan,np.nan],
                 'col_left':['a','b', np.nan,np.nan,np.nan,np.nan], 
-                'col_right':[np.nan, 2,2,2,2,2]}, 
+                'col_conflict_y':[np.nan,1,2,3,4,5], 
+                'col_right':[np.nan, 2,2,2,2,2]},
                 dtype='float64')
         df_result['_merge'] = pd.Categorical(['left_only','both','right_only',
             'right_only','right_only','right_only']
             , categories=['left_only', 'right_only', 'both'])
 
+        df_result = df_result[['col1', 'col_conflict_x', 'col_left', 
+                               'col_conflict_y', 'col_right', '_merge' ]]
+
         test = pd.merge(df1, df2, on='col1', how='outer', indicator=True)
         assert_frame_equal(test, df_result)
 
+
         # No side effects
         assert_frame_equal(df1, df1_copy)
         assert_frame_equal(df2, df2_copy)