sum() does not honor skipna argument
sum() is giving 0.0 as the total, rather than NaN, when the entire row/column is NaN.

Note that this bug does not arise in pandas 17.1 with numpy 1.11.0, running on Ubuntu.
#### Code Sample, a copy-pastable example if possible

```
import numpy as np
df = pd.DataFrame([[np.nan,np.nan,np.nan,np.nan],
              [1,np.nan,np.nan,np.nan],[2,2,2,np.nan]],columns=['a','b','c','d'])
df.sum(skipna=True)   # should be true by default. Same result if argument is omitted
```
#### Actual Output

a    3.0
b    2.0
c    2.0
d    0.0
#### Expected Output

a    3.0
b    2.0
c    2.0
d    NaN
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Darwin
OS-release: 15.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 23.1.0
Cython: 0.24
numpy: 1.11.1
scipy: 0.17.1
statsmodels: 0.6.1
xarray: None
IPython: 4.1.2
sphinx: None
patsy: 0.4.1
dateutil: 2.2
pytz: 2014.7
blosc: None
bottleneck: 1.1.0
tables: 3.2.2
numexpr: 2.6.0
matplotlib: 1.5.1
openpyxl: 2.3.4
xlrd: 0.9.4
xlwt: None
xlsxwriter: None
lxml: 3.6.0
bs4: 4.4.1
html5lib: 0.999
httplib2: 0.8
apiclient: 1.2
sqlalchemy: 1.0.12
pymysql: None
psycopg2: 2.5.4 (dt dec pq3 ext)
jinja2: 2.7.2
boto: 2.40.0
pandas_datareader: None
