title: nlargest on groupby with multiindex and multiple agg column
body: <p>Stuggling to apply .nlargest() to my groupedby data in order to only show the largest 10 by gross revenue per index[0]</p>
  
  <p>Groupedby data looks like this:</p>
  
  <p><a href="https://i.stack.imgur.com/PhoWk.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/PhoWk.png" alt="Data currently"></a></p>
  
  <p>when I run:</p>
  
  <pre><code>grp_data.n_largest(10,'GrossRevenue_GBP')
  </code></pre>
  
  <p>doesn't seem to be working for me, full code snippet is below:</p>
  
  <pre><code>tmean = lambda x :stats.trim_mean(x, 0.1)
  
  data = data.loc[(data['YYYY'] == 2016)&amp;(data['New_category_ID'] != 0)]
  
  grp_data = data.groupby(['New_category','CDI_CUS_NM'])['GrossRevenue_GBP',
  'OrderCount',
  '% Rev', 
  'MOVC_GBP', 
  'Average order size']
  .aggregate({'GrossRevenue_GBP':np.sum, 'OrderCount':np.sum,'% Rev': np.sum,'MOVC_GBP': tmean ,'Average order size': tmean })
  .nlargest(10,'GrossRevenue_GBP')
  
  
  grp_data['Country'] = 'EU'
  
  
  key1 = grp_data.index.labels[0]
  key2 = grp_data['GrossRevenue_GBP'].rank(ascending=False)
  sorter = np.lexsort((key2, key1))
  
  grp_data = grp_data.take(sorter)
  
  
  grp_data = grp_data[['% Rev','GrossRevenue_GBP', 'MOVC_GBP','Average order size','OrderCount','Country']]
  </code></pre>
  
  <p>Would really appreciate some help.</p>
  
  <p>Thanks,</p>