title: .agg Sum Converting NaN to 0
body: <p>I am trying to bin a Pandas DataFrame into three day windows. I have two columns, A and B, which I want to sum in each window. This code which I wrote for the task </p>
  
  <pre><code>    df = df.groupby(df.index // 3).agg({'A': 'sum', 'B':'sum'})
  </code></pre>
  
  <p>Converts NaN values to zero when doing this sum, but I would like them to remain NaN as my data has actual non-NaN zero values.</p>
  
  <p>For example if I had this df:</p>
  
  <pre class="lang-py prettyprint-override"><code>df = pd.DataFrame([
       [np.nan, np.nan],
       [np.nan, 0],
       [np.nan, np.nan],
       [2,   0],
       [4 ,  0],
       [0  , 0]
  ], columns=['A','B'])
  
  Index A   B
  0     NaN Nan
  1     NaN 3
  2     NaN Nan
  3     2   0
  4     4   0
  5     0   0
  </code></pre>
  
  <p>I would like the new df to be:</p>
  
  <pre><code>Index A   B
  0     NaN 3
  1     6   0
  </code></pre>
  
  <p>But my current code outputs:</p>
  
  <pre><code>Index A   B
  0     0   3
  1     6   0
  </code></pre>