title: Calculating difference between the min and max date and then compare it with current date value in pandas df
body: <p>I have campaign data where i want to find the runtime based on min, max and current date.
  For example: </p>
  
  <p>I have data like:</p>
  
  <pre><code>Date         Campaign     
  1.1.2020       A
  2.1.2020       A
  3.1.2020       A
  1.1.2020       B
  2.1.2020       B
  </code></pre>
  
  <p>I used min and max aggregation to find the min and max date value like this:</p>
  
  <pre><code> df_min_max_date = df.groupby('Campaign')['Date'].agg(['min', 'max']).reset_index()
  
      Date         Campaign       min               max
          1.1.2020       A      1.1.2020          3.1.2020  
          2.1.2020       A      1.1.2020          3.1.2020  
          3.1.2020       A      1.1.2020          3.1.2020  
          1.1.2020       B      1.1.2020          2.1.2020
          2.1.2020       B      1.1.2020          2.1.2020
  </code></pre>
  
  <p>But now i need another column which explain the runtime:
  The <strong>desired output</strong> would be like this</p>
  
  <pre><code> Date         Campaign       min               max     runtime
   1.1.2020       A      1.1.2020          3.1.2020       0%
   2.1.2020       A      1.1.2020          3.1.2020       50%
   3.1.2020       A      1.1.2020          3.1.2020       100%
   1.1.2020       B      1.1.2020          2.1.2020        0%
   2.1.2020       B      1.1.2020          2.1.2020       100%
  </code></pre>