python - Efficiently joining two dataframes based on multiple levels of a multiindex -
i have dataframe large multiindex, , secondary dataframe multiindex subset of larger one. secondary dataframe kind of lookup table. want add columns lookup table larger dataframe. primary dataframe large, want efficiently. here imaginary example, want join df2 df1: in [11]: arrays = [ ['sun', 'sun', 'sun', 'moon', 'moon', 'moon', 'moon', 'moon'], ....: ['summer', 'winter', 'winter', 'summer', 'summer', 'summer', 'winter', 'winter'], ....: ['one', 'one', 'two', 'one', 'two', 'three', 'one', 'two']] in [12]: tuples = list(zip(*arrays)) in [13]: index = pd.multiindex.from_tuples(tuples, names=['body', 'season','item']) in [14]: df1 = pd.dataframe(np.random.randn(8,2), index=index,columns=['a','b']) in [15]: df...