python - Merge two DataFrames based on multiple keys in pandas

Question

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

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

The desired result is:

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

Answer 1

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

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.