title: Insert rows as a result of a groupby operation into the original dataframe
body: <p>For example, I have a pandas dataframe as follows:</p>
  
  <pre><code>col_1   col_2   col_3  col_4
  a       X        5      1
  a       Y        3      2
  a       Z        6      4
  b       X        7      8
  b       Y        4      3
  b       Z        6      5
  </code></pre>
  
  <p>And I want to, for each value in col_1, add the values in col_3 and col_4 (and many more columns) that correspond to X and Z from col_2 and create a new row with these values. So the output would be as below:</p>
  
  <pre><code>col_1   col_2   col_3  col_4 
  a       X        5      1
  a       Y        3      2
  a       Z        6      4
  a       NEW      11     5
  b       X        7      8
  b       Y        4      3
  b       Z        6      5
  b       NEW      13     13
  </code></pre>
  
  <p>Also, there could be more values in col_1 that will need the same treatment, so I can't explicitly reference 'a' and 'b'. I attempted to use a combination of groupby('col_1') and apply(), but I couldn't get it to work. I'm close enough with the below, but I can't get it to put 'NEW' in col_2 and to keep the original value (a or b, etc.) in col_1.</p>
  
  <pre><code>df.append(df[(df['col_2'] == 'X') | (df['col_2'] == 'Z')].groupby('col_1').mean())
  </code></pre>
  
  <p>Thanks.</p>