Currently if you have a dataframe with a multiindex with a date as one of the indexers you can not save it as a frame_table. Use datetime instead.
Update: Thanks to Jeff again for the solution
import pandas as pd, numpy, datetime print pd.__version__ #-> 0.13.0rc1 idx1 = pd.MultiIndex.from_tuples([(datetime.date(2013,12,d), s, t) for d in range(1,3) for s in range(2) for t in range(3)]) df1 = pd.DataFrame(data=numpy.zeros((len(idx1),2)), columns=['a','b'], index=idx1) #-> If you want to save as a table in HDF5 use datetime rather than date with pd.get_store('test1.h5') as f: f.put('trials',df1) #-> OK with pd.get_store('test2.h5') as f: f.put('trials',df1,data_colums=True,format='t') #-> TypeError: [date] is not implemented as a table column #-> Solution is to use datetime
Update: Thanks to Jeff again for the solution
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