title: Pandas series stacked bar chart normalized
body: <p>I have a pandas series with a multiindex like this:</p>
  
  <pre><code>my_series.head(5)
  datetime_publication  my_category
  2015-03-31            xxx                  24
                        yyy                  2
                        zzz                  1
                        qqq                  1
                        aaa                  2
  dtype: int64
  </code></pre>
  
  <p>I am generating a horizontal bar chart using the <code>plot</code> method from <code>pandas</code> with all those stacked categorical values divided by datetime (according to the index hierarchy) like this:</p>
  
  <pre><code>my_series.unstack(level=1).plot.barh(
      stacked=True, 
      figsize=(16,6),
      colormap='Paired', 
      xlim=(0,10300), 
      rot=45
  )
  plt.legend(
      bbox_to_anchor=(0., 1.02, 1., .102), 
      loc=3, 
      ncol=5, 
      mode="expand", 
      borderaxespad=0.
  )
  </code></pre>
  
  <p>However I am not able to find a way to normalize all those values in the series broken down by <code>datetime_publication,my_category</code>. I would like to have <strong>all the horizontal bars of the same length</strong>, but right now the legth depends on the absolute values in the series.</p>
  
  <p><a href="https://i.stack.imgur.com/DxJbp.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/DxJbp.jpg" alt="horizontal bar chart - stacked"></a></p>
  
  <p>Is there a built-in functionality from pandas to normalize the slices of the series or some quick function to apply at the series that keeps track of the total taken from the multiindex combinatin of the levels?</p>