title: Seaborn workaround for hue barplot
body: <p>I have the following DataFrame on a <strong>Jupyter notebook</strong> which plots using seaborn a barplot:</p>
  <pre><code>data = {'day_index': [0, 1, 2, 3, 4, 5, 6],
          'avg_duration': [708.852242, 676.7021900000001, 684.572677, 708.92534, 781.767476, 1626.575057, 1729.155673],
          'trips': [114586, 120936, 118882, 117868, 108036, 43740, 37508]}
  
  df = pd.DataFrame(data)
  
  daysOfWeek = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
  
  plt.figure(figsize=(16,10));
  sns.set_style('ticks')
  ax = sns.barplot(data=df, \
                   x='day_index', \
                   y='avg_duration', \
                   hue='trips', \
                   palette=sns.color_palette(&quot;Reds_d&quot;, n_colors=7, desat=1))
  
  ax.set_xlabel(&quot;Week Days&quot;, fontsize=18, alpha=0.8)
  ax.set_ylabel(&quot;Duration (seconds)&quot;, fontsize=18, alpha=0.8)
  ax.set_title(&quot;Week's average Trip Duration&quot;, fontsize=24)
  ax.set_xticklabels(daysOfWeek, fontsize=16)
  ax.legend(fontsize=15)
  sns.despine()
  plt.show()
  </code></pre>
  <p><strong>Plot A:</strong>
  <a href="https://i.stack.imgur.com/JVOnC.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/JVOnC.png" alt="enter image description here" /></a></p>
  <p>As it can be seen the bars do not match the x_ticklabels and are very thin.<br />
  This is all fixed if I remove the <code>hue='trips'</code> part, it's a known seaborn issue.
  Although It's very important to show the amount of trips in the visualization so: <strong>is there a way around seaborn (maybe with matplotlib directly) to add a hue attribute?</strong></p>