title: Pandas: Sort dataframe by date string without converting
body: <p>Take this simple dataframe:</p>
  
  <pre><code>df = pd.DataFrame({
      'date':['1/15/2017', '2/15/2017','10/15/2016', '3/15/2017'], 
      'int':[2,3,1,4]
  })
  </code></pre>
  
  <p>I'd like to sort it by the date, and then save it to a CSV without having to:</p>
  
  <ol>
  <li>Convert dates using <code>pd.to_datetime(df['date'])</code></li>
  <li>Sort the dataframe using <code>.sort_values('date')</code></li>
  <li>Convert dates back to <code>.strftime('%-m/%-d/%Y')</code></li>
  </ol>
  
  <p>And instead do something like this (which of course, doesn't work):</p>
  
  <pre><code>df.apply(pd.to_dataframe(df['date']).sort_values(by = 'date', inplace = True)
  </code></pre>
  
  <p>Output:</p>
  
  <pre><code>         date  kw
  2  10/15/2016   1
  0   1/15/2017   2
  1   2/15/2017   3
  3   3/15/2017   4
  </code></pre>
  
  <p>Is this possible, or should I just stick with the 3-step process?</p>