连接具有相同 ID 的 Pandas DataFrame 行
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Concatenate rows of pandas DataFrame with same id
提问by Alex
Say I have a pandas DataFrame such as:
假设我有一个 Pandas DataFrame，例如：
A B id
0 1 1 0
1 2 1 0
2 3 2 1
3 0 2 1
Say I want to combine rows with the same id so that the other elements in the rows get put together in a list, so that the above dataframe would become:
假设我想组合具有相同 id 的行，以便行中的其他元素放在一个列表中，这样上面的数据框就会变成：
A B id
0 [1, 2] [1, 1] 0
1 [3, 0] [2, 2] 1
as the first two rows, and the last two rows have the same id. Does pandas have a function to do this? I am aware of the pandas groupby command, but I would like the return type to be a dataframe as well. Thanks.
作为前两行，后两行具有相同的 id。大Pandas有这样做的功能吗？我知道 pandas groupby 命令，但我希望返回类型也为数据帧。谢谢。
回答by Anton Protopopov
You could use groupbyfor that with groupby aggmethod and tolistmethod of Pandas Series:
您可以使用groupbygroupbyagg方法和tolistPandas 系列方法：
In [762]: df.groupby('id').agg(lambda x: x.tolist())
Out[762]:
A B
id
0 [1, 2] [1, 1]
1 [3, 0] [2, 2]
groupbyreturn an Dataframe as you want:
groupby根据需要返回数据框：
In [763]: df1 = df.groupby('id').agg(lambda x: x.tolist())
In [764]: type(df1)
Out[764]: pandas.core.frame.DataFrame
To exactly match your expected result you could additionally do reset_indexor use as_index=Falsein groupby:
要完全匹配您的预期结果，您还可以在以下内容中执行reset_index或使用：as_index=Falsegroupby
In [768]: df.groupby('id', as_index=False).agg(lambda x: x.tolist())
Out[768]:
id A B
0 0 [1, 2] [1, 1]
1 1 [3, 0] [2, 2]
In [771]: df1.reset_index()
Out[771]:
id A B
0 0 [1, 2] [1, 1]
1 1 [3, 0] [2, 2]
