title: Add missing rows to data frame equally distribueted
body: <p>I sampled a pandas dataframe using a custom sampler function. 
  This is basically made up by two columns:</p>
  
  <ul>
  <li>a timestamp</li>
  <li>a value</li>
  </ul>
  
  <p>I'd like to create a new data frame with all the datetimes equally distributed (i.e. every 10 minutes) to fill missing values in the sampled one (sampled at the same frequency). </p>
  
  <p>Shoudl I need to use the <em>reindex</em> method?</p>
  
  <p>I'm trying to do something like:</p>
  
  <pre><code>dd = pd.date_range(
          start_date.astimezone(pytz.utc),
          end_date.astimezone(pytz.utc),
          freq="3min"
  
      )
  dd = dd.map(lambda item: calendar.timegm(item.timetuple()))
  df.index = df.reindex(dd, fill_value="NaN")
  </code></pre>
  
  <p>It just does not works. I get a "length mismatch error" since the two indexes have different size.</p>
  
  <p>Is this the correct approach?</p>
  
  <p>Thanks, </p>
  
  <p>FB</p>