title: MultiIndex Group By with customize column conclusion in Pandas Data Frame
body: <p>I desire to achieve something we do in sql as follows:</p>
  
  <pre><code>SELECT Column1, Column2, mean(Column3), sum(Column4)
  FROM SomeTable
  GROUP BY Column1, Column2
  </code></pre>
  
  <pre><code>Store_Code  Brand_Code  Sales_Price
  
      1   18  28.00
      2   17  105.33
      2   17  65.33
      1   17  30.67
      1   18  6.67
  
  </code></pre>
  
  <p>As in above dataset I desire to group this dataframe with store code and taking most frequent brand code and sales price as it is or implementing some other operation like mean on sales price.</p>
  
  <p>Currently all I am able to do is apply one single operation to all columns.</p>
  
  <p><strong>something like this</strong></p>
  
  <pre><code>data.groupby(level=['Store_Code]).sum()
  </code></pre>
  
  <pre><code>Store_Code  Brand_Code  Sales_Price
  
      1   18  17.33
          17  30.67
  
      2   17  85.33
  
  </code></pre>