title: In Python/Pandas how do I convert century-months to DateTimeIndex?
body: <p>I am working with a dataset that encodes dates as the integer number of months since December 1899, so month 1 is January 1900 and month 1165 is January 1997.  I would like to convert to a pandas DateTimeIndex.  So far the best I've come up with is:</p>
  
  <pre><code>month0 = np.datetime64('1899-12-15')
  one_month = np.timedelta64(30, 'D') + np.timedelta64(10.5, 'h')
  birthdates = pandas.DatetimeIndex(month0 + one_month * resp.cmbirth)
  </code></pre>
  
  <p>The start date is the 15th of the month, and the timedelta is 30 days 10.5 hours, the average length of a calendar month.  So the date within the month drifts by a day or two.</p>
  
  <p>So this seems a little hacky and I wondered if there's a better way.</p>