title: Concatenate Pandas columns under new multi-index level
body: <p>Given a dictionary of data frames like:</p>
  
  <pre><code>dict = {'ABC': df1, 'XYZ' : df2}   # of any length...
  </code></pre>
  
  <p>where each data frame has the same columns and similar index, for example:</p>
  
  <pre><code>data           Open     High      Low    Close   Volume
  Date                                                   
  2002-01-17  0.18077  0.18800  0.16993  0.18439  1720833
  2002-01-18  0.18439  0.21331  0.18077  0.19523  2027866
  2002-01-21  0.19523  0.20970  0.19162  0.20608   771149
  </code></pre>
  
  <p>What is the simplest way to combine all the data frames into one, with a multi-index like:</p>
  
  <pre><code>symbol         ABC                                       XYZ
  data           Open     High      Low    Close   Volume  Open ...
  Date                                                   
  2002-01-17  0.18077  0.18800  0.16993  0.18439  1720833  ...
  2002-01-18  0.18439  0.21331  0.18077  0.19523  2027866  ...
  2002-01-21  0.19523  0.20970  0.19162  0.20608   771149  ...
  </code></pre>
  
  <p>I've tried a few methods - eg for each data frame replace the columns with a multi-index like <code>.from_product(['ABC', columns])</code> and then concatenate along <code>axis=1</code>, without success.</p>