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Pandas DataFrame 合并求和列

[英]Pandas DataFrame merge summing column

I'm trying to merge two DataFrames summing columns value.我正在尝试合并两个DataFrames求和列值。

>>> print(df1)
   id name  weight
0   1    A       0
1   2    B      10
2   3    C      10

>>> print(df2)
   id name  weight
0   2    B      15
1   3    C      10

I need to sum weight values during merging for similar values in the common column.在合并公共列中的相似值时,我需要对weight值求和。

merge = pd.merge(df1, df2, how='inner')

So the output will be something like following.所以输出将如下所示。

   id name  weight
1   2    B      25
2   3    C      20

This solution works also if you want to sum more than one column.如果您想对多列求和,此解决方案也适用。 Assume data frames假设数据帧

>>> df1
   id name  weight  height
0   1    A       0       5
1   2    B      10      10
2   3    C      10      15
>>> df2
   id name  weight  height
0   2    B      25      20
1   3    C      20      30

You can concatenate them and group by index columns.您可以连接它们并按索引列分组。

>>> pd.concat([df1, df2]).groupby(['id', 'name']).sum().reset_index()
   id name  weight  height
0   1    A       0       5
1   2    B      35      30
2   3    C      30      45
In [41]: pd.merge(df1, df2, on=['id', 'name']).set_index(['id', 'name']).sum(axis=1)
Out[41]: 
id  name
2   B       25
3   C       20
dtype: int64

If you set the common columns as the index, you can just sum the two dataframes, much simpler than merging:如果将公共列设置为索引,则可以将两个数据帧相加,比合并简单得多:

In [30]: df1 = df1.set_index(['id', 'name'])

In [31]: df2 = df2.set_index(['id', 'name'])

In [32]: df1 + df2
Out[32]: 
         weight
id name        
1  A        NaN
2  B         25
3  C         20

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