title: Python Pandas groupby forloop & Idxmax
body: <p>I have a DataFrame that must be grouped on three levels, and would then have the highest value returned. Each day there is a return for each unique value, and I would like to find the highest return and the details.</p>
  
  <pre><code>data.groupby(['Company','Product','Industry'])['ROI'].idxmax()
  </code></pre>
  
  <p>The return would show that:</p>
  
  <pre><code>Target   - Dish Soap - House       had a 5% ROI on 9/17
  Best Buy - CDs       - Electronics had a 3% ROI on 9/3
  </code></pre>
  
  <p>was the highest.</p>
  
  <p>Here's some example data:</p>
  
  <pre><code>+----------+-----------+-------------+---------+-----+
  | Industry | Product   | Industry    | Date    | ROI |
  +----------+-----------+-------------+---------+-----+
  | Target   | Dish Soap | House       | 9/17/13 | 5%  |
  | Target   | Dish Soap | House       | 9/16/13 | 2%  |
  | BestBuy  | CDs       | Electronics | 9/1/13  | 1%  |
  | BestBuy  | CDs       | Electroincs | 9/3/13  | 3%  |
  | ...
  </code></pre>
  
  <p>Not sure if this would be a for loop, or using .ix.</p>