title: Pandas DataFrame: Can't iterate over Grouped Series
body: <p>So I have the following Panda Series <code>grouped</code>:</p>
  
  <pre><code>                               Amount
  Ticker Unit   Date       Time        
  FLWS   SHARES 2019-01-03 -       20.0
                2019-01-13 -       20.0
  PIH    SHARES 2019-01-13 -      -10.0
         VALUE  2019-01-03 -      -25.0
  </code></pre>
  
  <p>*I wanted to reset the index to remove the 'Amount' as a multi-index and "drop-it-down" but then the grouping becomes unstacked and this only after the Series is converted to a DataFrame. </p>
  
  <p>I am trying to iterate over the groups:</p>
  
  <pre><code>    for ticker, action, date, time in grouped:
          print(ticker)
          print(action)
          print(date)
          print(time)
  </code></pre>
  
  <p>but I get the following: <code>TypeError: 'float' object is not iterable</code></p>
  
  <p>ADDITIONAL INFO:
  I get the mentioned dataframe from the following:</p>
  
  <pre><code>orders = pd.DataFrame(OrderedDict([
          ('Ticker', tickers),
          ('Action', actions),
          ('Unit', units),
          ('Amount', amounts),
          ('Date', dates),
          ('Time', times),
      ]))
  
      df_orders = pd.DataFrame(orders)
  if not df_orders.empty:
      df_orders.loc[df_orders['Action'] == 'SELL', 'Amount'] *= -1
      grouped = df_orders.groupby(['Ticker', 'Unit', 'Date', 'Time'])['Amount'].apply(np.sum) 
  
      print(grouped)
  </code></pre>
  
  <p>where <code>tickers</code>, <code>actions</code>, <code>units</code>, etc are all lists</p>
  
  <p>EDIT: 
  I figured it would be best to show the logic in which I wanted to handle the acquired data. </p>
  
  <pre><code>total = 0
  for ticker in tickers: 
      for date in dates:    
          if unit=='SHARES':
              total += some_function(ticker, date)
          else:
              total += some_function(ticker, date)  
  </code></pre>
  
  <p>notice in this case, every ticker in tickers would be unique. So how would you iterate over the grouped series in this manner?  </p>