BUG: NaN in DataFame column causes select with condition to always return empty
```
import pandas as pd, numpy

r = numpy.array([
[1,2],
[2,1],
[1,2],
[2,1]],dtype=float)
r[0,1] = numpy.nan

df = pd.DataFrame(data=r,columns=['s1','s2'])
print 'Original:'
print df
print 'Selected:'
print df[df.s2==1]

# As expected
#   s1  s2
#1   2   1
#3   2   1

df.to_hdf('float_bug.h5','data',table=True,data_columns=['s1','s2'])
with pd.get_store('float_bug.h5') as store:
  print 'Selected store'
  print store.select('data',['s2=1'])

# Unexpected
# Empty DataFrame
#Columns: [s1, s2]
#Index: []

In [72]: pd.__version__
Out[72]: '0.12.0'
```

You can verify this does not happen in the column without the NaN or when there are no NaNs at all.
