title: Count the individual values within the arrays stored in a pandas Series
body: <p>Here's a simple example to set the stage:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  
  example_series = pd.Series([np.arange(5), 
                              np.arange(15), 
                              np.arange(12), 
                              np.arange(7), 
                              np.arange(3)])
  print example_series
  
  0                                      [0, 1, 2, 3, 4]
  1    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...
  2               [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
  3                                [0, 1, 2, 3, 4, 5, 6]
  4                                            [0, 1, 2]
  </code></pre>
  
  <p>I've got a pandas Series (example_series) that contains a bunch of arrays. I'm trying to count the number of instances each number appears in the series. So, I'm hoping to return something that looks like: </p>
  
  <pre><code># Counts = 
  0:5
  1:5
  2:5
  3:4
  4:4
  5:3
  #...and so on
  </code></pre>
  
  <p>And I'd prefer that it returned a Series, but it's OK if it's something else. This seems simple enough, but I can't figure it out. I'll post a few failed attempts below. </p>
  
  <pre><code># None of these work
  example_series.count(0)
  example_series.count(lambda x: x == 0)
  example_series[example_series == 0]
  example_series.unique()
  </code></pre>
  
  <p>Thanks for any help!</p>