Merge multi-indexed with single-indexed data frames in pandas

Question

I have two dataframes. df1 is multi-indexed:

                value
first second    
a     x         0.471780
      y         0.774908
      z         0.563634
b          


        

Answer 1

According to the documentation, as of pandas 0.14, you can simply join single-index and multiindex dataframes. It will match on the common index name. The how argument works as expected with 'inner' and 'outer', though interestingly it seems to be reversed for 'left' and 'right' (could this be a bug?).

df1 = pd.DataFrame([['a', 'x', 0.471780], ['a','y', 0.774908], ['a', 'z', 0.563634],
                    ['b', 'x', -0.353756], ['b', 'y', 0.368062], ['b', 'z', -1.721840],
                    ['c', 'x', 1], ['c', 'y', 2], ['c', 'z', 3],
                   ],
                   columns=['first', 'second', 'value1']
                   ).set_index(['first', 'second'])
df2 = pd.DataFrame([['a', 10], ['b', 20]],
                   columns=['first', 'value2']).set_index(['first'])

print(df1.join(df2, how='inner'))
                value1  value2
first second                  
a     x       0.471780      10
      y       0.774908      10
      z       0.563634      10
b     x      -0.353756      20
      y       0.368062      20
      z      -1.721840      20