title: How to transform a pandas dataframe to multiindex dataframe
body: <p>I have time series pandas dataframe which i would like to transform to a multiindex dataframe with one column.</p>
  
  <p>Here is the dataframe:</p>
  
  <pre><code>Date         MMM             ABT             ABBV            ABMD
  20171017    -0.004455   0.007810    0.012260    0.011132
  20171018    0.002382    0.012731    0.040296    0.002775
  20171019    0.004424    0.004107    0.004561    -0.00429
  20171020    0.009398    0.005682    -0.003954   0.013801
  </code></pre>
  
  <p>I tried this code:</p>
  
  <pre><code>for date in returns.index:
  
      arrays = [[[date] * len(returns.columns)][0], 
      list(returns.columns)]
      tuples = list(zip(*arrays))
      index = pd.MultiIndex.from_tuples(tuples)
      multi.loc[(date,np.array(index.levels[1])),:] = 
      returns.loc[date,:].values.reshape(-1,1)
  </code></pre>
  
  <p>however i get the following error :</p>
  
  <pre><code>TypeError: unhashable type: 'numpy.ndarray'
  </code></pre>
  
  <p>I expected to have:</p>
  
  <pre><code>                    Returns
   20171017   MMM  -0.004455
              ABT  0.007810
              ABBV     0.012260
              ABMD     0.011132
              ACN  -0.003173
              ATVI     0.002919
              ADBE     -0.000532
              AMD  -0.007062
              AAP  0.023612
              AES  -0.007149
              AMG  -0.007792
              AFL  -0.005014
              A    -0.011948
              APD  0.001629
              AKAM     -0.002966
              ALK  0.000621
  </code></pre>