合并后，Pandas Dataframe列会隐式转换为Nan

Question

以下是我的2个pandas数据帧的小样本：

    In [65]: df1
 Out[65]:
          Send_Agent  Send_Amount Country_Code
 0     AWD120279        85.99          KW
 1     API185805        22.98          PH
 2     ANO080012       490.00          NO
 3     AUK359401       616.16          GB
 4     ACL000105       193.78          CL


 In [44]: df2
Out[44]:
Country_Code  Rating
0         KW Medium
1         PH Higher
2         NO Lower
3         GB Lower
4         CL Lower

In [97]: df4 = df1[df1['Send_Agent']=='AWD120279']

In [98]: df4
Out[98]:
 Send_Agent  Send_Amount Country_Code
0     AWD120279        85.99          KW
3359  AWD120279       200.00          KW
3878  AWD120279       203.03          KW

In [102]: df5 =  df2[df2['Country_Code']=='KW']
In [104]: df5
 Out[104]:
           Country_Code  Rating
  15           KW         Medium


    In [105]: pd.merge(df4,df5,on='Country_Code',how='left')
Out[105]:
Send_Agent  Send_Amount Country_Code Rating
0  AWD120279        85.99          KW     NaN
1  AWD120279       200.00          KW     NaN
2  AWD120279       203.03          KW     NaN

我无法弄清楚为什么“评级”列在合并后会转换为Nan。每个Country_Code都有与之关联的评级。所以，它永远不应该是南。