使用 Full Outer Join 合并两个数据帧未在两个数据帧上获取 Key Column

Merging two data frames not getting Key Column on both dataframes with Full OuterJoin

我有两个如下所示的数据框。我使用 pandas 和 numpy 来比较差异。

df_a
               Key                           Value
0       data_owner                            John
1     locationcode                           local
2             Unit                           sales
3      application                       autosales


df_b 
               Key                           Value
0       data_owner                            John
1     locationcode                           local
2             Unit                           sales
3      application                       autosales
4       department                     frontoffice

我正在使用以下代码进行合并

 df = pd.merge(df_a,df_b,on=['Key'],how='outer',left_index=True,right_index=True)

 df['diff'] = np.where((df['Value_x']==df['Value_y']), 'No', 'Yes')

我打算输出比较 df 和两侧的任何缺失项目应该输出。

下面的实际输出:但问题是我想显示两个数据帧中的键,但是如果你看到下面的输出它只显示一次,即我需要 Key_y 也是输出的一部分。

              Key                         Value_x                          Value_y   diff
0       data_owner                            John                            John   No
1     locationcode                           local                           local   No
2             unit                           sales                           sales   No
3      application                       autosales                       autosales   No
4       department                     frontoffice                             NaN   No

预期输出:我想显示来自两个

的密钥
            Key_x                          Value_x       Key_y                    Value_y    diff
0       data_owner                            John       data_owner                  John    No
1     locationcode                           local       locationcode               local    No
2             unit                           sales       unit                       sales    No
3      application                       autosales       application            autosales    No
4       department                     frontoffice       NaN                          NaN    Yes

使用,DataFrame.add_suffix在合并之前将后缀添加到两个数据框的列中,这样它们的键在合并后就不会组合成单个列:

df = pd.merge(
    df_b.add_suffix('_x'), df_a.add_suffix('_y'), 
    left_on='Key_x', right_on='Key_y', how='outer')

df['diff'] = np.where(df['Value_x'].eq(df['Value_y']), 'No', 'Yes')

# print(df)
          Key_x      Value_x         Key_y    Value_y diff
0    data_owner         John    data_owner       John   No
1  locationcode        local  locationcode      local   No
2          Unit        sales          Unit      sales   No
3   application    autosales   application  autosales   No
4    department  frontoffice           NaN        NaN  Yes