title: How can I reindex pandas dataframe to reset the starting index value to zero？
body: <p>In my dataframe, there are NaN values in some rows. I want to delete these rows. I solve it with dataframe.dropna(how='any'). The result looks like:</p>
  
  <pre><code>         date  time   open   hign    low  close  volume  turnover
  2  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
  3  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508
  </code></pre>
  
  <p>I want to reindex the rows of my dataframe, so I run:</p>
  
  <pre><code>length = dataframe.dropna(how='any').shape[0]
  dataframe1 = dataframe.index(range(length))
  </code></pre>
  
  <p>But dataframe1 still keeps the old index values, like：</p>
  
  <pre><code>          date  time   open   hign    low  close  volume  turnover
  0         NaN   NaN    NaN    NaN    NaN    NaN     NaN       NaN
  1         NaN   NaN    NaN    NaN    NaN    NaN     NaN       NaN
  2  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
  3  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508
  </code></pre>
  
  <p>How can I make the number begin with 0 and delete the first two rows?</p>
  
  <p>Desired result:</p>
  
  <pre><code>          date  time   open   hign    low  close  volume  turnover
  0  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
  1  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508
  </code></pre>