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