我认为您可以使用 aggregate

I think you can use groupby with aggregate first and custom function ', '.join:

df = df.groupby('Name').agg({'Sid':'first', 
                             'Use_Case': ', '.join, 
                             'Revenue':'first' }).reset_index()

#change column order                           
print df[['Name','Sid','Use_Case','Revenue']]                              
  Name   Sid           Use_Case Revenue
0    A  xx01         Voice, SMS  $10.00
1    B  xx02              Voice   $5.00
2    C  xx03  Voice, SMS, Video  $15.00

评论中的好主意，谢谢 Goyo :

Nice idea from comment, thanks Goyo:

df = df.groupby(['Name','Sid','Revenue'])['Use_Case'].apply(', '.join).reset_index()

#change column order                           
print df[['Name','Sid','Use_Case','Revenue']]                              
  Name   Sid           Use_Case Revenue
0    A  xx01         Voice, SMS  $10.00
1    B  xx02              Voice   $5.00
2    C  xx03  Voice, SMS, Video  $15.00