title: Duplicate column Pandas dataframe slice issue
body: <p>I have a dataframe <code>df</code> with duplicate columns: (I need duplicate columns dataframe, which will be passed as a parameter to matplotlib to plot, so the columns' name and content might be same or different) </p>
  
  <pre><code>&gt;&gt;&gt; df
                                           PE     RT    Ttl_mkv      PE
  STK_ID    RPT_Date                                  
  11_STK79  20130115  41.932  2.744   3629.155  41.932
  21_STK58  20130115  14.223  0.048  30302.324  14.223
  22_STK229 20130115  22.436  0.350  15968.313  22.436
  23_STK34  20130115 -63.252  0.663   4168.189 -63.252
  </code></pre>
  
  <p>I can get the second column by : <code>df[df.columns[1]]</code>  , </p>
  
  <pre><code>&gt;&gt;&gt; df[df.columns[1]]
  STK_ID     RPT_Date
  11_STK79   20130115    2.744
  21_STK58   20130115    0.048
  22_STK229  20130115    0.350
  23_STK34   20130115    0.663
  </code></pre>
  
  <p>but if I want to get the first column by <code>df[df.columns[0]]</code> , it will give :</p>
  
  <pre><code>&gt;&gt;&gt; df[df.columns[0]]
                                     PE      PE
  STK_ID    RPT_Date                
  11_STK79  20130115  41.932  41.932
  21_STK58  20130115  14.223  14.223
  22_STK229 20130115  22.436  22.436
  23_STK34  20130115 -63.252 -63.252
  </code></pre>
  
  <p>Which one has two columns? That will make my application down for the application just wants the first column but Pandas give 1st &amp; 4th column!  Is it a bug or it is designed as this on purpose ? How to bypass this  issue ? </p>
  
  <p>My pandas version is 0.8.1 .</p>