HDF read query issue
I created an HDF file using:

```
X.to_hdf('test.hdf', 'X', format='t', data_columns=['date', 'evaluation'])
```

I am interested in reading rows matching a query:

```
where = "((date >= '2010-01-01' and date < '2012-01-01') & (evaluation > 0)) | (date == '2012-01-01')"
```

However running

```
pd.read_hdf('test.hdf', 'X', where=where)
```

Does not return all matching rows. If I alternatively run 

```
pd.read_hdf('test.hdf', 'X').query(where)
```

I get the correct rows.
#### Code Sample, a copy-pastable example if possible

I uploaded my example to this [repository](https://github.com/potash/pandas-hdf-select-bug). After cloning the repository unzip the buggy HDF files:

```
unzip test.zip
```

The `test.hdf` file is the one producing the bug, but the `test2.hdf`-- which only differs by removing all columns except the ones used in the query-- but does not produce the bug!

You can test the two hdf files using `python test.py test.hdf` and `python test.py test2.hdf`.
#### Expected Output

Both runs should print

```
29540
29540
```
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-91-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.1
pip: 8.1.2
setuptools: 24.0.2
Cython: None
numpy: 1.11.1
scipy: 0.13.3
statsmodels: 0.5.0
xarray: None
IPython: 4.2.0
sphinx: None
patsy: 0.2.1
dateutil: 2.2
pytz: 2012c
blosc: None
bottleneck: None
tables: 3.1.1
numexpr: 2.6.0
matplotlib: 1.3.1
openpyxl: 2.2.0-b1
xlrd: 0.9.2
xlwt: 0.7.5
xlsxwriter: None
lxml: None
bs4: 4.2.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: 2.4.5 (dt dec mx pq3 ext)
jinja2: 2.8
boto: 2.20.1
pandas_datareader: None
