read_hdf / store.select modifies the passed columns parameters when multi-indexed

[eldad-a]

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'

[jreback]

hmm, not sure their any guarantees on this, but makes sense to simply copy this and not modify.

Want to do a pull-request?

[eldad-a]

my current solution is to pass a copy:

df_ = pd.read_hdf(h5name, key, columns= list(cols2load))

BTW, the same problem holds for the where parameter of read_hdf.
I do not expect to be able to do the pull-request soon (it'll be my first, so it will take time...).
I mainly thought it is worth posting as I wasted quite some time on finding the "bug" in my code.
Turned out it wast this (I was using cols2load for several different purposes in the code).

[jreback]

no problem

take your time

about to release 0.14.0 in any event

[jreback]

@eldad-a if you have a pull-request for this would be great

[eldad-a]

@jreback unfortunately i do not expect to be able to get into the matter soon.
In case I will, I'll defenitely submit a pull-request.

[jreback]

ok, thanks