title: Pandas: Group by two columns to get sum of another column
body: <p>I look most of the previously asked questions but was not able to find answer for my question: </p>
  
  <p>I have following data.frame</p>
  
  <pre><code>           id   year month score num_attempts
  0      483625  2010    01   50      1
  1      967799  2009    03   50      1
  2      213473  2005    09  100      1
  3      498110  2010    12   60      1
  5      187243  2010    01  100      1
  6      508311  2005    10   15      1
  7      486688  2005    10   50      1
  8      212550  2005    10  500      1
  10     136701  2005    09   25      1
  11     471651  2010    01   50      1
  </code></pre>
  
  <p>I want to get following data frame </p>
  
  <pre><code>year month sum_score sum_num_attempts
  2009    03   50           1
  2005    09  125           2
  2010    12   60           1
  2010    01  200           2
  2005    10  565           3
  </code></pre>
  
  <p>Here is what I tried: </p>
  
  <pre><code>sum_df = df.groupby(by=['year','month'])['score'].sum()
  </code></pre>
  
  <p>But this doesn't look efficient and correct. If I have more than one column need to be aggregate this seems like a very expensive call. for example if I have another column <code>num_attempts</code> and just want to sum by year month as score. </p>