title: Detect duplicated groups with Pandas
body: <p>I have a table with a Date field and I would like to detect days where data is not duplicated. Let's imagine the data is like the following:</p>
  
  <pre><code>Day        Code Value
  01/03/2020  A   10
  01/03/2020  B   15
  01/03/2020  C   20
  02/03/2020  A   10
  02/03/2020  B   15
  02/03/2020  C   20
  03/03/2020  A   10
  03/03/2020  B   20
  03/03/2020  C   20
  04/03/2020  A   10
  04/03/2020  B   15
  </code></pre>
  
  <p>I would like to group the data by days. In the example, day 02/03/2020 is the same than 01/03/2020. However, in day 03/03/2020 the value of B has changed. Also, in day 04/03/2020 code C has dissapeared.</p>
  
  <p>The first approach I see is to loop through the data filtering the dataset by day (a) and compare the result with the slice of the day before (b) by checking if <code>a.equals(b)</code> is <code>TRUE</code>. I know this works but it is not efficient at all as implies a lot of slicing.</p>
  
  <p>Is there any <code>group_by</code> operation that could do the task?</p>
  
  <p>Thank you very much.</p>