pandas -数据框分组-如何获取多个列的总和 [英] Pandas - dataframe groupby - how to get sum of multiple columns

问题描述

这应该很简单，但是以某种方式我找不到有效的解决方案.

This should be an easy one, but somehow I couldn't find a solution that works.

我有一个熊猫数据框，看起来像这样:

I have a pandas dataframe which looks like this:

index col1   col2   col3   col4   col5
0     a      c      1      2      f 
1     a      c      1      2      f
2     a      d      1      2      f
3     b      d      1      2      g
4     b      e      1      2      g
5     b      e      1      2      g

我想按col1和col2分组并获得col3和col4的sum().由于无法汇总数据，可以删除Col5.

这是输出的外观.我对在结果数据帧中同时包含col3和col4感兴趣. col1和col2是否属于索引并不重要.

Here is how the output should look like. I am interested in having both col3 and col4 in the resulting dataframe. It doesn't really matter if col1 and col2 are part of the index or not.

index col1   col2   col3   col4   
0     a      c      2      4          
1     a      d      1      2      
2     b      d      1      2      
3     b      e      2      4      

这是我尝试过的:

df_new = df.groupby(['col1', 'col2'])["col3", "col4"].sum()

但是，这只会返回col4的汇总结果.

That however only returns the aggregated results of col4.

我在这里迷路了.我发现的每个示例仅汇总一列，显然不会发生问题.

I am lost here. Every example I found only aggregates one column, where the issue obviously doesn't occur.

推荐答案

通过使用apply

df.groupby(['col1', 'col2'])["col3", "col4"].apply(lambda x : x.astype(int).sum())
Out[1257]: 
           col3  col4
col1 col2            
a    c        2     4
     d        1     2
b    d        1     2
     e        2     4

如果要agg

df.groupby(['col1', 'col2']).agg({'col3':'sum','col4':'sum'})

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