title: Pandas pivot table - show values under same column index
body: <p>I am having trouble with constructing a Pandas pivot table. 
  I wish to have two values <code>['Balance', 'WAP']</code> under the same column <code>['Delivery']</code>.</p>
  
  <p>Here is the DataFrame constructed from a dictionary:</p>
  
  <pre><code>dict_data = {
      'Contract' : ['Contract 1', 'Contract 2', 'Contract 3', 'Contract 4'],
      'Contract_Date': ['01/01/2019', '02/02/2019', '03/03/2019', '04/03/2019'],
      'Delivery' : ['2019-01', '2019-01', '2019-02', '2019-03'],
      'Price' : [90, 95, 100, 105],
      'Balance': [50, 100, 150, 200]
  }
  
  df = pd.DataFrame.from_dict(dict_data)
  
  df
  </code></pre>
  
  <p>The DataFrame:</p>
  
  <pre><code>    Contract    Contract_Date   Delivery    Price   Balance
  0   Contract 1  01/01/2019       2019-01    90      50
  1   Contract 2  02/02/2019       2019-01    95      100
  2   Contract 3  03/03/2019       2019-02    100     150
  3   Contract 4  04/03/2019       2019-03    105     200
  </code></pre>
  
  <p>Calculate weighted average price:</p>
  
  <pre><code># Create WAP - Weighted Average Price
  df['Value'] = df['Balance'] * df['Price'] 
  df['WAP'] = df['Value'] / df['Balance']
  df
  </code></pre>
  
  <p>Pivot table construction:</p>
  
  <pre><code># Use a dictionary to apply more than 1 type of aggregate onto the data
  f = {'Balance': ['sum'], 'WAP': ['mean']}
  
  df.pivot_table(
      columns='Delivery',
      values=['Balance', 'WAP'],
      index=['Contract_Date', 'Contract'],
      aggfunc=f
  ).replace(np.nan, '')
  </code></pre>
  
  <p><img src="https://i.imgur.com/3k1X62s.png" alt="pivot">
  I am trying to get the 2 values to show up under the same column, for easier comparison, like the below table (manually constructed):</p>
  
  <pre><code>              Delivery   2019-01          2019-02          2019-03 
  Contract Date Contract   Balance     WAP  Balance   WAP    Balance     WAP 
  01/01/2019    Contract 1 50          90      
  02/02/2019    Contract 2 100         95     
  03/03/2019    Contract 3                  150       100
  04/03/2019    Contract 4                                   200         105
  </code></pre>
  
  <p>Am thinking somewhere along the lines of stack/unstack for this problem? Would greatly appreciate any help as I am still rather new to Pandas..</p>