title: Pandas dropping columns by index drops all columns with same name
body: <p>Consider following dataframe which has columns with same name (Apparently this does happens, currently I have a dataset like this! :( )</p>
  
  <pre><code>&gt;&gt;&gt; df = pd.DataFrame({"a":range(10,15),"b":range(5,10)})
  &gt;&gt;&gt; df.rename(columns={"b":"a"},inplace=True)
  df
  
      a   a
  0   10  5
  1   11  6
  2   12  7
  3   13  8
  4   14  9
  
  &gt;&gt;&gt; df.columns
  Index(['a', 'a'], dtype='object')
  </code></pre>
  
  <p>I would expect that when dropping by index , only the column with the respective index would be gone, but apparently this is not the case.</p>
  
  <pre><code>&gt;&gt;&gt; df.drop(df.columns[-1],1)
  
  0
  1
  2
  3
  4
  </code></pre>
  
  <p>Is there a way to get rid of columns with duplicated column names? </p>
  
  <p><strong>EDIT: I choose missleading values for the first column, fixed now</strong></p>
  
  <p><strong>EDIT2: the expected outcome is</strong></p>
  
  <pre><code>  a
  0 10
  1 11
  2 12 
  3 13
  4 14
  </code></pre>