Sum across NaNs yields zero?
I'm running pandas 0.17.0 and was surprised by this behavior, which seems inconsistent with the docs (I expected to get NaN, not zero, at index 2). If I substitute "None" for "np.nan", I get the same result, but I get the expected result--NaN--if I use "NaT". Wondering if I've stumbled on a bug . . . 

```
In [136]: df = pd.DataFrame()

In [137]: df['a'] = [1,2,np.nan,3]

In [138]: df['b'] = [4,5,np.nan,6]

In [139]: df
Out[139]: 
   a   b
0   1   4
1   2   5
2 NaN NaN
3   3   6

In [140]: df['total'] = df.sum(axis=1)

In [141]: df
Out[141]: 
   a   b  total
0   1   4      5
1   2   5      7
2 NaN NaN      0
3   3   6      9
```
