title: Fill rmultiple ows in between pandas dataframe rows on condition
body: <p>I have a dataframe, where I have date wise withdraw/credit and closing balance information.</p>
  
  <pre><code>date      withdraw     credit    closing_balance
  02/06/17    2,500.00      nan           6,396.77
  03/06/17      nan      36,767.00       43,163.77
  05/06/17    1,770.00      nan          41,393.77
  05/06/17     6000.00      nan           35393.77
  05/06/17      278.00      nan           35115.77
  07/06/17     1812.00      nan           33303.77
  </code></pre>
  
  <p>Now we can see that we have 2 days entries missing in this table.
  i.e <strong>04/06/17 and 06/06/17</strong>. Since there were no transactions on that day.</p>
  
  <p>What I'm looking to do is add dummy rows in the dataframe for these dates, 4th and 6th, with </p>
  
  <p>withdraw column as <strong>0</strong>, credit column as <strong>0</strong>,</p>
  
  <p>And closing balance column as the same of the last closing balance entry of the previous day.</p>
  
  <p>Expected output</p>
  
  <pre><code>date      withdraw     credit    closing_balance
  02/06/17    2,500.00      nan           6,396.77
  03/06/17      nan      36,767.00       43,163.77
  04/06/17     nan(or 0)  nan(or 0)      43,163.77
  05/06/17    1,770.00      nan          41,393.77
  05/06/17     6000.00      nan           35393.77
  05/06/17      278.00      nan           35115.77
  06/06/17    nan(or 0)   nan(or 0)       35115.77
  07/06/17     1812.00      nan           33303.77
  </code></pre>
  
  <p>Is there a pythonic way of doing this.</p>
  
  <p>What i thought was to first find the missing dates, then create a ttemporary dataframe for those dates and then concatenate it with the main dataframe and then sort.</p>
  
  <p>But I'm having issue in how to get the previous days last closing balance entry, to fill in the missing days closing balance.</p>