python - Pandas HDFStore: Saving and Retrieving a Series with Hierarchical Period Index -

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i first create series 2 dimensional hierarchical index. index type (pandas.period, numpy.int32)

in [265]: import pandas pd  in [266]: import numpy np  in [267]: hdf_file = r'f:\test.h5'  in [268]: data = np.random.randint(10, size=(7, 3))  in [269]: dates = pd.date_range('1/1/2015', '1/7/2015').to_period('d')  in [270]: ts1 = pd.dataframe(data, index = dates, columns = [1, 2, 3]).stack()

then, save series (ts1) using hdfstore , retrieve (as ts2):

in [271]: pd.hdfstore(hdf_file, 'w') store:      ...:     store['ts'] = ts1      ...:       in [272]: pd.hdfstore(hdf_file, 'r') store:      ...:     ts2 = store['ts']      ...:

now, dtype of index of retrieved series (ts2) has been changed integer:

in [273]: print(ts1) 2015-01-01  1    3             2    8             3    0 2015-01-02  1    2             2    3             3    9 2015-01-03  1    9             2    2             3    2 2015-01-04  1    4             2    5             3    1 2015-01-05  1    2             2    1             3    6 2015-01-06  1    1             2    0             3    8 2015-01-07  1    0             2    6             3    8 dtype: int32  in [274]: print(ts2) 16436  1    3        2    8        3    0 16437  1    2        2    3        3    9 16438  1    9        2    2        3    2 16439  1    4        2    5        3    1 16440  1    2        2    1        3    6 16441  1    1        2    0        3    8 16442  1    0        2    6        3    8 dtype: int32

is there way save series properly? know can change type after retrieve data, prefer job cleanly.

i using pandas 0.16.1 , pyhon 2.7.7 (anaconda 2.0.1 (64-bit))

this not implemented see issue here

save timestamps , convert periods after read back


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