Pandas 如何强制应用以返回父数据帧的所有列？

在数据帧的某些列上使用groupby并随后使用apply测试另一列中是否存在字符串后，pandas仅返回按分组的列以及使用apply创建的最后一列。是否可以返回与groupby和test关联的所有列？例如，通过会话线程的唯一标识符进行分组，并测试字符串是否存在于另一列中，但随后是否包括存在于数据帧中但属于特定组的其他列

我尝试过使用groupby，然后使用apply作为匿名函数

df.head()

 shipment_id shipper_id courier_id  Question                                sender
0   14      9962    228898  Let's get your furbabys home Apple pet transpo...   courier
1   91919   190872  196838  Hi I'm kevin thims and I'm happy to do the job...   courier
2   92187   191128  196838  Hi I'm kevin thims and I'm happy to do the job...   shipper

unique_thread_indentifier = ['shipment_id', 'shipper_id', 'courier_id']
required_variables = ['shipment_id', 'shipper_id', 'courier_id', 'Question', 'sender']

df_new = (
    df
    .groupby(unique_thread_indentifier)[required_variables]
    .apply(lambda group: 'shipper' in group['sender'].unique())
    .to_frame(name='shipper_replied')
    .reset_index()
)

df_new.head()
    shipment_id shipper_id  courier_id  shipper_replied
0   14      9962            228898          False
1   91919   190872          196838          False
2   92187   191128          196838          True

我的目标是将

Question

和

sender

列包含在最后的数据帧中。预期输出如下所示：

 shipment_id shipper_id courier_id  Question                                sender        shipper_replied
0   14      9962    228898  Let's get your furbabys home Apple pet transpo...   courier       False
1   91919   190872  196838  Hi I'm kevin thims and I'm happy to do the job...   courier       False
2   92187   191128  196838  Hi I'm kevin thims and I'm happy to do the job...   shipper       True

我相信你需要：

另一个解决方案：

df['shipper_replied'] = (df.assign(new = df['sender'].eq('shipper'))
                           .groupby(unique_thread_indentifier)['new']
                           .transform('any'))

print (df)
   shipment_id  shipper_id  courier_id  \
0           14        9962      228898   
1        91919      190872      196838   
2        92187      191128      196838   

                                          Question   sender  shipper_replied  
0  Let's get your furbabys home Apple pet transpo.  courier            False  
1   Hi I'm kevin thims and I'm happy to do the job  courier            False  
2   Hi I'm kevin thims and I'm happy to do the job  shipper             True  

---

您可以将预期输出添加到问题中吗？这不是我想要的-我希望将列

question

包含到结果数据框中，如预期的那样output@homeStayProg-你现在能查一下吗？

df['shipper_replied'] = (df.assign(new = df['sender'].eq('shipper'))
                           .groupby(unique_thread_indentifier)['new']
                           .transform('any'))

print (df)
   shipment_id  shipper_id  courier_id  \
0           14        9962      228898   
1        91919      190872      196838   
2        92187      191128      196838   

                                          Question   sender  shipper_replied  
0  Let's get your furbabys home Apple pet transpo.  courier            False  
1   Hi I'm kevin thims and I'm happy to do the job  courier            False  
2   Hi I'm kevin thims and I'm happy to do the job  shipper             True