title: Seaborn barplot with rounded corners
body: <p>I'm trying to plot some bars but would like to control the roundness of the corners.  I tried following the answer provided in stack question <a href="https://stackoverflow.com/questions/58425392/bar-chart-with-rounded-corners-in-matplotlib">Bar chart with rounded corners in Matplotlib</a> but can't seem to get the same result. How can I get the bars to have rounded edges with control to the roundness? Also is there a better alternative FancyBboxPatch?</p>
  
  <p>Below is my testable code along with the current and desired output.</p>
  
  <p><strong>My Code:</strong></p>
  
  <pre><code>import pandas as pd
  import matplotlib.pyplot as plt
  import seaborn as sns
  from matplotlib.patches import FancyBboxPatch
  
  mydict = {
      'Event': ['Running', 'Swimming', 'Biking', 'Hiking'],
      'Completed': [2, 4, 3, 7],
      'Participants': [10, 20, 35, 10]}
  
  df = pd.DataFrame(mydict).set_index('Event')
  df = df.assign(Completion=(df.Completed / df.Participants) * 100)
  print(df)
  
  plt.subplots(figsize=(5, 2))
  
  sns.set_color_codes("pastel")
  ax = sns.barplot(x=df.Completion, y=df.index, orient='h', joinstyle='bevel')
  
  new_patches = []
  for patch in reversed(ax.patches):
      bb = patch.get_bbox()
      color = patch.get_facecolor()
      p_bbox = FancyBboxPatch((bb.xmin, bb.ymin),
                              abs(bb.width), abs(bb.height),
                              boxstyle="round,pad=-0.0040,rounding_size=0.015",
                              ec="none", fc=color,
                              mutation_aspect=4
                              )
      patch.remove()
      new_patches.append(p_bbox)
  
  for patch in new_patches:
      ax.add_patch(patch)
  
  sns.despine(left=True, bottom=True)
  ax.tick_params(axis=u'both', which=u'both', length=0)
  plt.tight_layout()
  plt.show()
  </code></pre>
  
  <p><strong>Example DataFrame:</strong></p>
  
  <pre><code>          Completed  Participants  Completion
  Event                                        
  Running           2            10   20.000000
  Swimming          4            20   20.000000
  Biking            3            35    8.571429
  Hiking            7            10   70.000000
  </code></pre>
  
  <p><strong>Current Output:</strong></p>
  
  <p><a href="https://i.stack.imgur.com/Irm9b.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Irm9b.png" alt="enter image description here"></a></p>
  
  <p><strong>Desired Output:</strong></p>
  
  <p><a href="https://i.stack.imgur.com/dOUa0.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/dOUa0.png" alt="enter image description here"></a></p>