title: reading dates using python read_csv with seperator / or - and years less than 1968
body: <p>I have twoissues regarding reading dates using read_csv in python</p>
  
  <ol>
  <li><p>How to read dates that have mixed format ? The dates are in the form dd/mm/yy , dd-mm-yy , dd/mm/yyyy or dd-mm-yyyy</p></li>
  <li><p>there are some dates in the years lesser than or equal to 1968. How to preserve the century information so that date comparisions can be performed correctly.</p></li>
  </ol>
  
  <pre><code>df = pd.read_csv('train.csv',dayfirst=True,parse_dates=['DoB','DisDt'])
  </code></pre>
  
  <p>I have also tried using date_parser</p>
  
  <pre><code>dtpse = lambda x:pd.datetime.strptime(x,'%d/%m/%y')
  df = pd.read_csv('train.csv',dayfirst=True,parse_dates=['DoB','DisDt'],date_parser=dtpse)
  </code></pre>
  
  <p>The dates are in the form given below in the csv file</p>
  
  <pre><code>01/01/2008
  01/01/74
  12-04-2004
  12-04-1968
  01/06/1978
  </code></pre>
  
  <p>I am trying to use python read_csv to get the results shown below</p>
  
  <p><b>Expected Results</b></p>
  
  <pre><code>01-01-2008
  01-01-74
  12-04-2004
  12-04-1968
  01-06-1978
  </code></pre>
  
  <p>The main aim is to store the century information so that while subtracting dates the correct difference is calculated .</p>