Merge pull request #11154 from chris-b1/merge-indicator-method

ENH: add merge indicator to DataFrame.merge

Author: jreback

pandas/core/frame.py

@@ -4265,12 +4265,12 @@ def _join_compat(self, other, on=None, how='left', lsuffix='', rsuffix='',
     @Appender(_merge_doc, indents=2)
     def merge(self, right, how='inner', on=None, left_on=None, right_on=None,
               left_index=False, right_index=False, sort=False,
-              suffixes=('_x', '_y'), copy=True):
+              suffixes=('_x', '_y'), copy=True, indicator=False):
         from pandas.tools.merge import merge
         return merge(self, right, how=how, on=on,
                      left_on=left_on, right_on=right_on,
                      left_index=left_index, right_index=right_index, sort=sort,
-                     suffixes=suffixes, copy=copy)
+                     suffixes=suffixes, copy=copy, indicator=indicator)
 
     def round(self, decimals=0, out=None):
         """

pandas/tools/tests/test_merge.py

@@ -951,25 +951,27 @@ def test_indicator(self):
         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], 
+
+        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_conflict_y':[np.nan,1,2,3,4,5], 
+                'col_left':['a','b', np.nan,np.nan,np.nan,np.nan],
+                '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', 
+        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)
+        test = df1.merge(df2, on='col1', how='outer', indicator=True)
+        assert_frame_equal(test, df_result)
 
         # No side effects
         assert_frame_equal(df1, df1_copy)
@@ -981,49 +983,65 @@ def test_indicator(self):
 
         test_custom_name = pd.merge(df1, df2, on='col1', how='outer', indicator='custom_name')
         assert_frame_equal(test_custom_name, df_result_custom_name)
+        test_custom_name = df1.merge(df2, on='col1', how='outer', indicator='custom_name')
+        assert_frame_equal(test_custom_name, df_result_custom_name)
 
         # Check only accepts strings and booleans
         with tm.assertRaises(ValueError):
             pd.merge(df1, df2, on='col1', how='outer', indicator=5)
+        with tm.assertRaises(ValueError):
+            df1.merge(df2, on='col1', how='outer', indicator=5)
 
         # Check result integrity
-    
+
         test2 = pd.merge(df1, df2, on='col1', how='left', indicator=True)
         self.assertTrue((test2._merge != 'right_only').all())
+        test2 = df1.merge(df2, on='col1', how='left', indicator=True)
+        self.assertTrue((test2._merge != 'right_only').all())
 
         test3 = pd.merge(df1, df2, on='col1', how='right', indicator=True)
         self.assertTrue((test3._merge != 'left_only').all())
+        test3 = df1.merge(df2, on='col1', how='right', indicator=True)
+        self.assertTrue((test3._merge != 'left_only').all())
 
         test4 = pd.merge(df1, df2, on='col1', how='inner', indicator=True)
         self.assertTrue((test4._merge == 'both').all())
+        test4 = df1.merge(df2, on='col1', how='inner', indicator=True)
+        self.assertTrue((test4._merge == 'both').all())
 
         # Check if working name in df
         for i in ['_right_indicator', '_left_indicator', '_merge']:
             df_badcolumn = pd.DataFrame({'col1':[1,2], i:[2,2]})
-        
+
             with tm.assertRaises(ValueError):
                 pd.merge(df1, df_badcolumn, on='col1', how='outer', indicator=True)
+            with tm.assertRaises(ValueError):
+                df1.merge(df_badcolumn, on='col1', how='outer', indicator=True)
 
         # Check for name conflict with custom name
         df_badcolumn = pd.DataFrame({'col1':[1,2], 'custom_column_name':[2,2]})
-        
+
         with tm.assertRaises(ValueError):
             pd.merge(df1, df_badcolumn, on='col1', how='outer', indicator='custom_column_name')
+        with tm.assertRaises(ValueError):
+            df1.merge(df_badcolumn, on='col1', how='outer', indicator='custom_column_name')
 
         # Merge on multiple columns
         df3 = pd.DataFrame({'col1':[0,1], 'col2':['a','b']})
 
         df4 = pd.DataFrame({'col1':[1,1,3], 'col2':['b','x','y']})
 
-        hand_coded_result = pd.DataFrame({'col1':[0,1,1,3.0], 
+        hand_coded_result = pd.DataFrame({'col1':[0,1,1,3.0],
                                          'col2':['a','b','x','y']})
         hand_coded_result['_merge'] = pd.Categorical(
             ['left_only','both','right_only','right_only']
             , categories=['left_only', 'right_only', 'both'])
- 
+
         test5 = pd.merge(df3, df4, on=['col1', 'col2'], how='outer', indicator=True)
         assert_frame_equal(test5, hand_coded_result)
-    
+        test5 = df3.merge(df4, on=['col1', 'col2'], how='outer', indicator=True)
+        assert_frame_equal(test5, hand_coded_result)
+
 
 def _check_merge(x, y):
     for how in ['inner', 'left', 'outer']: