title: How to compare and group paired values across groups pandas
body: <p>Apologies if something similar has been asked before, I searched around but couldn't figure out a solution.</p>
  <p>My data looks like this, except with many more subjects (Math, Science, History, etc):</p>
  <pre><code>data = {'Group':['Winner','Winner','Loser','Loser'],
          'MathStudy': ['Read','Read','Notes','None'],'ScienceStudy': ['Tutor','Read','None','Notes'],
          'MathScore':[90,100,40,50],'ScienceScore':[100,100,40,50]}
  df = pd.DataFrame(data=data)
  </code></pre>
  <p><a href="https://i.stack.imgur.com/ouT55.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/ouT55.png" alt="enter image description here" /></a></p>
  <p>Each row is a student, and I'd like to see which method of studying ( Tutor/Read/Notes/None) results in the best average score, based on group.</p>
  <p>I would like to have an average over all subjects. Example: Reading results in an average score of 95 across all subjects in the Winner group, compared to 60 in the Loser group.</p>
  <p>Any help or pointers are appreciated, thank you!</p>