title: Most efficient way to convert date strings to a pandas time series index
body: <p>My CSV data file contains dates in the following format:</p>
  
  <pre><code>In: data["DayIndex"].unique()
  
  Out: array(['04/23/17', '04/20/17', '04/21/17', '04/24/17', '04/22/17',
         '05/02/17', '04/27/17', '05/06/17', '04/30/17', '04/25/17',
         '04/26/17', '05/04/17'], dtype=object)    
  </code></pre>
  
  <p>I want to turn it into a proper pandas time series. I've tried this:</p>
  
  <pre><code>data["DayIndex"] = pandas.DatetimeIndex(data["Day"])
  </code></pre>
  
  <p>It takes ages even for a few hundred thousand rows. What are my options to speed up the parsing?</p>