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

You could use get_level_values:

firsts = df1.index.get_level_values('first')
df1['value2'] = df2.loc[firsts].values

Note: you are almost doing a join here (except the df1 is MultiIndex)… so there may be a neater way to describe this…

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In an example (similar to what you have):

df1 = pd.DataFrame([['a', 'x', 0.123], ['a','x', 0.234],
                    ['a', 'y', 0.451], ['b', 'x', 0.453]],
                   columns=['first', 'second', 'value1']
                   ).set_index(['first', 'second'])
df2 = pd.DataFrame([['a', 10],['b', 20]],
                   columns=['first', 'value']).set_index(['first'])

firsts = df1.index.get_level_values('first')
df1['value2'] = df2.loc[firsts].values

In [5]: df1
Out[5]: 
              value1  value2
first second                
a     x        0.123      10
      x        0.234      10
      y        0.451      10
b     x        0.453      20