title: rolling_sum on business day and return new dataframe with date as index
body: <p>I have such a <code>DataFrame</code>:</p>
  
  <pre><code>                     A
  2016-01-01 00:00:00  0
  2016-01-01 12:00:00  1
  
  2016-01-02 00:00:00  2
  2016-01-02 12:00:00  3
  2016-01-03 00:00:00  4
  2016-01-03 12:00:00  5
  
  2016-01-04 00:00:00  6
  2016-01-04 12:00:00  7
  2016-01-05 00:00:00  8
  2016-01-05 12:00:00  9
  </code></pre>
  
  <p>The reason I separate <strong>2016-01-02 00:00:00</strong> to <strong>2016-01-03 12:00:00</strong> is that, those two days are <strong>weekends</strong>.</p>
  
  <hr>
  
  <p>So here is what I wish to do:</p>
  
  <p>I wish to <code>rolling_sum</code> with <code>window = 2 business days</code>.</p>
  
  <p>For example, I wish to sum </p>
  
  <pre><code>                     A
  2016-01-04 00:00:00  6
  2016-01-04 12:00:00  7
  2016-01-05 00:00:00  8
  2016-01-05 12:00:00  9
  </code></pre>
  
  <p>and then sum (we skip any non-business days)</p>
  
  <pre><code>                     A
  2016-01-01 00:00:00  0
  2016-01-01 12:00:00  1
  
  2016-01-04 00:00:00  6
  2016-01-04 12:00:00  7
  </code></pre>
  
  <p>And the result is </p>
  
  <pre><code>                     A
  2016-01-01           Nan
  2016-01-04           14
  2016-01-05           30
  </code></pre>
  
  <hr>
  
  <p>How can I achieve that?</p>
  
  <p>I tried <code>rolling_sum(df, window=2, freq=BDay(1))</code>, it seems it just pick one row of the same day, but not sum the two rows (00:00 and 12:00) within the same day.</p>