Modules operation on DataFrame return -0 result.
#### Code Sample, a copy-pastable example if possible

import pandas as pd
import numpy as np

dates = pd.date_range('20160101', periods=12)
df = pd.DataFrame(np.random.randn(12, 4), index=dates, columns=list('ABCD'))
df.sort_index(axis=1, ascending=False) % df.sort_index(axis=1, ascending=True)

Output : -
                    A  B  C  D
2016-01-01  0 -0  0 -0
2016-01-02 -0  0  0  0
2016-01-03  0  0  0 -0
2016-01-04  0  0  0  0
2016-01-05  0 -0 -0  0
2016-01-06  0 -0  0  0
2016-01-07 -0 -0  0  0
2016-01-08  0  0 -0 -0
2016-01-09 -0 -0 -0 -0
2016-01-10 -0 -0 -0  0
2016-01-11 -0  0 -0  0
2016-01-12  0 -0 -0 -0
#### Expected Output

```
                A  B  C  D
```

2016-01-01  0  0  0  0
2016-01-02  0  0  0  0
2016-01-03  0  0  0  0
2016-01-04  0  0  0  0
2016-01-05  0  0  0  0
2016-01-06  0  0  0  0
2016-01-07  0  0  0  0
2016-01-08  0  0  0  0
2016-01-09  0  0  0  0
2016-01-10  0  0  0  0
2016-01-11  0  0  0  0
2016-01-12  0  0  0  0
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.5-300.fc23.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.17.1
nose: 1.3.7
pip: 7.1.0
setuptools: 20.10.1
Cython: None
numpy: 1.9.2
scipy: 0.14.1
statsmodels: None
IPython: 3.2.1
sphinx: 1.2.3
patsy: None
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: 0.6.0
tables: 3.2.2
numexpr: 2.4.6
matplotlib: 1.4.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.4.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
Jinja2: None
