基于 pandas 中的多个键合并两个DataFrame [英] Merge two DataFrames based on multiple keys in pandas

问题描述

pandas(或另一个模块)是否具有任何功能来支持基于多个键的两个表的合并(或联接)?

Does pandas (or another module) have any functions to support merge (or join) two tables based on multiple keys?

例如，我有两个表(DataFrames)a和b:

For example, I have two tables (DataFrames) a and b:

>>> a
A  B  value1
1  1      23
1  2      34
2  1    2342
2  2     333

>>> b
A  B  value2
1  1    0.10
1  2    0.20
2  1    0.13
2  2    0.33

所需的结果是:

A  B  value1  value2
1  1      23    0.10
1  2      34    0.20
2  1    2342    0.13
2  2     333    0.33

推荐答案

要通过多个键合并，只需要将列表中的键传递给

To merge by multiple keys, you just need to pass the keys in a list to pd.merge:

>>> pd.merge(a, b, on=['A', 'B'])
   A  B  value1  value2
0  1  1      23    0.10
1  1  2      34    0.20
2  2  1    2342    0.13
3  2  2     333    0.33

实际上，pd.merge的默认设置是使用两个DataFrame的列标签的交集，因此pd.merge(a, b)在这种情况下同样可以很好地工作.

In fact, the default for pd.merge is to use the intersection of the two DataFrames' column labels, so pd.merge(a, b) would work equally well in this case.

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