title: how to create a Dataframe (multi-index) with sub-columns from a nested Dictionary?
body: <p>I tried to create two sub-columns under one column. First I created a DataFrame from a Dictionary </p>
  
  <pre class="lang-py prettyprint-override"><code>Destination = ['Milan', 'London','Lisbon','Milan','Mumbai', 'Lisbon', 'Porto', 'Lisbon']
  Product_Revenue = [542,332,135,524,232, 522, 122, 122]
  
  data_frame = {'Destination' : [i for i in Destination], 
                              'Revenue': [j for j in Product_Revenue]}
  pd.DataFrame(data_frame)
  
  </code></pre>
  
  <p>Second, I wanted to add <code>Booking</code> as the main column so that <code>Destination</code> and <code>Revenue</code> becomes sub-column of it. But I got <code>Destination</code> and <code>Revenue</code> in the index and even as a list.</p>
  
  <pre class="lang-py prettyprint-override"><code>data_frame = {'Booking': {'Destination' : [i for i in Destination], 
                              'Revenue': [j for j in Product_Revenue]}}
  pd.DataFrame(data_frame)
  </code></pre>
  
  <pre><code>                             Booking
  
  Destination    [Milan, London, Vienna, Milan, Mumbai, Paris, ...
  
  
  Revenue     [542, 332, 135, 524, 232, 522, 122, 122]
  </code></pre>
  
  <p>The <code>Destination</code> and <code>Revenue</code> is showing in rows. </p>
  
  <p>How can I write each value of both in parallel as the previous one?</p>
  
  <p>A future goal is to add <code>Users</code> as the index. So, the final dataframe would be <code>User</code> Vs <code>Booking</code> Data where <code>Destination</code> and <code>Price</code> values would vary for each user. </p>
  
  <p>Any help would be highly appreciated.</p>