code to reproduce:
import pandas as pd
import numpy as np
## generate data
df = pd.DataFrame(np.random.rand(4,5), index=list('abcd'), columns=list('ABCDE'))
df.index.name = 'letters'
df = df.set_index(keys='E' , append=True)
## save to hdf5
h5name = 'tst.h5'
key = 'tst_key'
df.to_hdf(h5name, key,
mode='a', append=True,
data_columns = df.index.names+df.columns.tolist(),
index=False,
complevel=5, complib='blosc',
#expectedrows = expectedrows ,
)
## load part of df
cols2load = list('BCD')
print 'before loading: \n\t cols2load = {}'.format(cols2load)
df_ = pd.read_hdf(h5name, key, columns= cols2load)
print 'after loading: \n\t cols2load = {}'.format(cols2load)
The printed output:
before loading:
cols2load = ['B', 'C', 'D']
after loading:
cols2load = ['E', 'letters', 'B', 'C', 'D']
pd.version = '0.13.1'
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