title: Count Categorical data monthly Pandas
body: <p>I'm trying to count categorical data and plot the % of high, med, low for each month.</p>
  
  <p>It should look like this image below:</p>
  
  <p><a href="https://i.stack.imgur.com/rXgiS.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/rXgiS.png" alt="enter image description here"></a></p>
  
  <p>I have a data frame with Date and Score which looks like this below</p>
  
  <pre><code>-------------------------------
  |Date                 | Score  |
  |2016-1-02 00:00:00   | High   |
  |2016-2-02 00:00:00   | Low    |
  |2016-4-23 00:00:00   | Med    |
  |2016-5-03 00:00:00   | High   |
  |2016-6-02 00:00:00   | High   |
  |2016-6-04 00:00:00   | Low    |
  |2016-7-02 00:00:00   | Med    |
  |2016-12-02 00:00:00  | High   |
  -------------------------------
  </code></pre>
  
  <p>I know i can do this to get the split of each one but i dont know how to split this by month and then count each of these </p>
  
  <pre><code> df.groupby('Score').size()
  
   Score:
   High: 5
   Med: 15
   Low: 155
  </code></pre>
  
  <p>Thank you</p>