title: Pivoting first level of a multilevel index to be the first level of a multilevel column
body: <p>I have a multilevel index dataframe like this:</p>
  <pre><code>indx = [('location', 'a'), ('location', 'b'), ('location', 'c'), ('location2', 'a'), ('location2', 'b'), ('location2', 'c')]
  indx = pd.MultiIndex.from_tuples(indx)
  col = ['S1','S2','S3']
  df = pd.DataFrame(np.random.randn(6, 3), index=indx, columns=col)
  
  df
  
                     S1        S2        S3
  location  a -0.453549 -0.079797  0.581657
            b -0.458573 -0.732625 -2.277674
            c  0.874403  0.459590 -1.220271
  location2 a -1.418821  0.847556  0.665808
            b  1.321825 -0.150274  0.507685
            c  0.894865 -0.502577  2.460591
  </code></pre>
  <p>and I'm trying to move the first level of the index to be the first level of a multilevel column to look like this:</p>
  <pre><code>header = [np.array(['location','location','location','location2','location2','location2']),
  np.array(['S1','S2','S3','S1','S2','S3'])]
  df = pd.DataFrame(np.random.randn(3, 6), index=['a','b','c'], columns = header )
  
  df
  
     location                     location2                    
           S1        S2        S3        S1        S2        S3
  a  1.225889 -0.547848 -0.413482 -1.038456 -1.055484 -0.143620
  b -1.278012  0.403767 -0.298525  0.198157  0.327973 -0.088555
  c -1.152128  0.209956  0.939142  0.458412  1.207760 -0.091029
  </code></pre>
  <p>Any ideas?</p>