pandas 分组多个列，多个列的列表 [英] Pandas groupby multiple columns, list of multiple columns

问题描述

我有以下数据:

Invoice NoStockCode Description                         Quantity    CustomerID  Country
536365  85123A      WHITE HANGING HEART T-LIGHT HOLDER  6           17850       United Kingdom
536365  71053       WHITE METAL LANTERN                 6           17850       United Kingdom
536365  84406B      CREAM CUPID HEARTS COAT HANGER      8           17850       United Kingdom

我正在尝试进行分组，因此我需要执行以下操作:

I am trying to do a groupby so i have the following operation:

df.groupby(['InvoiceNo','CustomerID','Country'])['NoStockCode','Description','Quantity'].apply(list)

我想获取输出

|Invoice |CustomerID |Country        |NoStockCode              |Description                                                                                 |Quantity       
|536365| |17850      |United Kingdom |85123A, 71053, 84406B    |WHITE HANGING HEART T-LIGHT HOLDER, WHITE METAL LANTERN, CREAM CUPID HEARTS COAT HANGER     |6, 6, 8            

相反，我得到了:

|Invoice |CustomerID |Country        |0         
|536365| |17850      |United Kingdom |['NoStockCode','Description','Quantity']

我尝试了agg和其他方法，但是我无法让所有列都作为列表加入.我不需要使用列表功能，但是最后，我希望其他列成为列表.

I have tried agg and other methods, but I haven't been able to get all of the columns to join as a list. I don't need to use the list function, but in the end I want the different columns to be lists.

推荐答案

我现在无法重现您的代码，但我认为:

I can't reproduce your code right now, but I think that:

print (df.groupby(['InvoiceNo','CustomerID','Country'], 
                  as_index=False)['NoStockCode','Description','Quantity']
          .agg(lambda x: list(x)))

会给您期望的输出

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