Pandas - dataframe groupby - how to get sum of multiple columns : <p>This should be an easy one, but somehow I couldn't find a solution that works.</p>

<p>I have a pandas dataframe which looks like this:</p>

<pre><code>index col1   col2   col3   col4   col5
0     a      c      1      2      f 
1     a      c      1      2      f
2     a      d      1      2      f
3     b      d      1      2      g
4     b      e      1      2      g
5     b      e      1      2      g
</code></pre>

<p><strong>I want to group by col1 and col2 and get the <code>sum()</code> of col3 and col4.</strong> <code>Col5</code> can be dropped, since the data can not be aggregated.</p>

<p>Here is how the output should look like. I am interested in having both <code>col3</code> and <code>col4</code> in the resulting dataframe. It doesn't really matter if <code>col1</code> and <code>col2</code> are part of the index or not.</p>

<pre><code>index col1   col2   col3   col4   
0     a      c      2      4          
1     a      d      1      2      
2     b      d      1      2      
3     b      e      2      4      
</code></pre>

<p>Here is what I tried:</p>

<pre><code>df_new = df.groupby(['col1', 'col2'])["col3", "col4"].sum()
</code></pre>

<p>That however only returns the aggregated results of <code>col4</code>.</p>

<p>I am lost here. Every example I found only aggregates one column, where the issue obviously doesn't occur.</p>
