title: Pandas sum two columns, skipping NaN
body: <p>If I add two columns to create a third, any columns containing NaN (representing missing data in my world) cause the resulting output column to be NaN as well. Is there a way to skip NaNs without explicitly setting the values to 0 (which would lose the notion that those values are "missing")?</p>
  
  <pre><code>In [42]: frame = pd.DataFrame({'a': [1, 2, np.nan], 'b': [3, np.nan, 4]})
  
  In [44]: frame['c'] = frame['a'] + frame['b']
  
  In [45]: frame
  Out[45]: 
      a   b   c
  0   1   3   4
  1   2 NaN NaN
  2 NaN   4 NaN
  </code></pre>
  
  <p>In the above, I would like column c to be [4, 2, 4].</p>
  
  <p>Thanks...</p>