title: Sum across all NaNs in pandas returns zero?
body: <p>I'm trying to sum across columns of a Pandas dataframe, and when I have NaNs in every column I'm getting sum = zero; I'd expected sum = NaN based on the docs. Here's what I've got:</p>
  
  <pre><code>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
  </code></pre>
  
  <p>The pandas.DataFrame.sum docs say "If an entire row/column is NA, the result will be NA", so I don't understand why "total" = 0 and not NaN for index 2. What am I missing?</p>