Missing data and np.seterr(all='raise'): Viewing the missing yields FloatingPointError
#### Code Sample, a copy-pastable example if possible

```
import numpy as np
import pandas as pd
np.seterr(all='raise')

s = pd.Series([np.nan,np.nan,np.nan],index=[1,2,3]); print(s); print(s.head())
```
#### Expected Output

Certainly not a FloatingPointError:
`FloatingPointError: invalid value encountered in greater.`

The issue appears to lie in numpy, as 

`np.array([np.nan, np.nan]) > 1e8`

also raises the error. I have cross-posted the issue [there](https://github.com/numpy/numpy/issues/7352), but thought you guys also would want to be aware of this.
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Linux
OS-release: 3.19.0-49-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.17.1
nose: None
pip: 8.0.3
setuptools: 20.1.1
Cython: None
numpy: 1.10.4
scipy: 0.16.0
statsmodels: None
IPython: 4.0.1
sphinx: None
patsy: None
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: None
tables: None
numexpr: 2.5
matplotlib: 1.5.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
Jinja2: None
