title: Counting common elements in a list on that occur on same day in a pandas dataframe
body: <p>I have a DataFrame which looks like:</p>
  
  <pre><code>Users               Date
  ['A', 'B']        2017-10-21
  ['B', 'C']        2017-10-21
  ['A', 'D']        2017-10-21
  ['D', 'E']        2017-10-22
  ['A', 'E']        2017-10-22
  ['A', 'E', 'D']   2017-10-22
  ['C', 'B', 'E']   2017-10-23
  ['D', 'C', 'F']   2017-11-23
  </code></pre>
  
  <p>I need to make a new DataFrame from this DataFrame which would count the number of times the items show up in the list on each day. The count, therefore, would be across different rows on the same date..</p>
  
  <p>For example, the new DataFrame would look like:</p>
  
  <pre><code>Users                        Date
  [A=2, B=2, C=1, D=1]        2017-10-21
  [E=3, D=2, A=2]             2017-10-22
  [B=1, C=2, D=1, E=1, F=1]   2017-10-23
  </code></pre>
  
  <p>Some things to note: the all the items in the first dataset are lists with individual elements being strings. The Date column is of DateTime type.</p>
  
  <p>I understand there would be a <code>groupby</code> function on the <code>Date</code> column but I can't figure out how to write the function that I would <code>apply</code> to.</p>