title: Pandas Groupby date index and count values in list of integers
body: <p>I have the below data which is a date index that has date range between '2014-08-22' and '2014-08-28' and one column with list of integers. I am trying to figure out a nice Pandas method for just grouping the numbers by date. Desired Result also below. </p>
  
  <p>Date:</p>
  
  <pre><code>                                                                                values
  date                                                                                        
  2014-08-22                 [179, 187, 188, 190, 194, 198, 2, 226, 26, 311, 322, 325, 341, 6]
  2014-08-22                 [179, 187, 188, 190, 194, 198, 2, 226, 26, 311, 322, 325, 341, 6]
  2014-08-22  [167, 172, 178, 189, 198, 2, 20, 211, 212, 22, 274, 276, 287, 318, 321, 326, 48]
  2014-08-23  [167, 172, 178, 189, 198, 2, 20, 211, 212, 22, 274, 276, 287, 318, 321, 326, 48]
  2014-08-23  [167, 172, 178, 189, 198, 2, 20, 211, 212, 22, 274, 276, 287, 318, 321, 326, 48]
  </code></pre>
  
  <p>Desired pivot/groupby/crosstab Output:</p>
  
  <pre><code>      2014-08-22  2014-08-23
  179       2           0
  167       1           2
  etc... 
  </code></pre>
  
  <p>I know how to create a dict with the counts of occurrence as below but not sure how to group it by the index</p>
  
  <pre><code>from collections import Counter
  values_list = list(chain.from_iterable(df['values']))
  Counter(values_list)
  </code></pre>