串联具有相同ID的Pandas DataFrame行 [英] Concatenate rows of pandas DataFrame with same id

问题描述

说我有一个熊猫DataFrame，例如:

Say I have a pandas DataFrame such as:

   A  B  id
0  1  1   0
1  2  1   0
2  3  2   1
3  0  2   1

说我想合并具有相同id的行，以便将行中的其他元素放到一个列表中，这样上面的数据框将变为:

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:

     A       B     id
0  [1, 2]  [1, 1]   0
1  [3, 0]  [2, 2]   1

作为前两行，后两行具有相同的ID.熊猫有功能吗?我知道pandas groupby命令，但是我也希望返回类型也是一个数据框.谢谢.

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.

推荐答案

您可以使用

You could use groupby for that with groupby agg method and tolist method of Pandas Series:

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]

groupby根据需要返回一个数据框:

groupby return an Dataframe as you want:

In [763]: df1 = df.groupby('id').agg(lambda x: x.tolist())

In [764]: type(df1)
Out[764]: pandas.core.frame.DataFrame

要完全符合您的预期结果，您可以另外执行reset_index或在groupby中使用as_index=False:

To exactly match your expected result you could additionally do reset_index or use as_index=False in groupby:

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]

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