title: Pandas: changing dataframe date index format
body: <p>Would like to change the Date index of the dataframe from the default style into '%m/%d/%Y' format. </p>
  
  <pre><code>In: df
  Out: 
  
    Date     Close     
  
  2006-01-24  48.812471
  2006-01-25  47.448712
  2006-01-26  53.341202
  2006-01-27  58.728122
  2006-01-30  59.481986
  2006-01-31  55.691974
  </code></pre>
  
  <p>df.index</p>
  
  <pre><code> Out: 
   DatetimeIndex(['2006-01-04', '2006-01-05', '2006-01-06', '2006-01-09',
             '2006-01-10', '2006-01-11', '2006-01-12', '2006-01-13',
             '2006-01-17', '2006-01-18',
             ...
             '2018-02-21', '2018-02-22', '2018-02-23', '2018-02-26',
             '2018-02-27', '2018-02-28', '2018-03-01', '2018-03-02',
             '2018-03-05', '2018-03-06'],
            dtype='datetime64[ns]', name=u'Date', length=3063, freq=None)
  </code></pre>
  
  <p>Into:</p>
  
  <pre><code>In: df1
  Out: 
  
   Date     Close     
  
  01/24/2006  48.812471
  01/25/2006  47.448712
  01/26/2006  53.341202
  01/27/2006  58.728122
  01/28/2006  59.481986
  01/29/2006  55.691974
  </code></pre>
  
  <p>I tried this method before...</p>
  
  <pre><code> df1.index = pd.to_datetime(df.index, format = '%m/%d/%Y')
   df1.index = df.dt.strftime('%Y-%m-%d')
  
   AttributeError: 'DataFrame' object has no attribute 'dt'
  </code></pre>