python - Convert dataframe columns to MultiIndex -

how convert existing dataframe single-level columns have hierarchical index columns (multiindex)?

example dataframe:

in [1]: import pandas pd pandas import series, dataframe  df = dataframe(np.arange(6).reshape((2,3)),                index=['a','b'],                columns=['one','two','three']) df out [1]:    1  2  3    0    1      2 b    3    4      5 

i'd have thought reindex() work, nan's:

in [2]: df.reindex(columns=[['odd','even','odd'],df.columns]) out [2]:    odd     odd    1   2  3  nan   nan    nan b  nan   nan    nan 

same if use dataframe():

in [3]: dataframe(df,columns=[['odd','even','odd'],df.columns]) out [3]:    odd     odd    1   2  3  nan   nan    nan b  nan   nan    nan 

this last approach work if specify df.values:

in [4]: dataframe(df.values,index=df.index,columns=[['odd','even','odd'],df.columns]) out [4]:    odd     odd    1   2  3    0     1      2 b    3     4      5 

what's proper way this? why reindex() give nan's?

you close, set columns directly new (equal sized) index-like (which if list-of-list convert multi-index)

in [8]: df out[8]:     1  2  3    0    1      2 b    3    4      5  in [10]: df.columns = [['odd','even','odd'],df.columns]  in [11]: df out[11]:     odd     odd    1   2  3    0     1      2 b    3     4      5 

reindex reorder / filter existing index. reason nans saying, hey find existing columns match new index; none match, that's get