content: """
  Violinplot from a wide-form dataset
  ===================================
  
  _thumb: .6, .45
  """
  import seaborn as sns
  import matplotlib.pyplot as plt
  sns.set(style="whitegrid")
  
  # Load the example dataset of brain network correlations
  df = sns.load_dataset("brain_networks", header=[0, 1, 2], index_col=0)
  
  # Pull out a specific subset of networks
  used_networks = [1, 3, 4, 5, 6, 7, 8, 11, 12, 13, 16, 17]
  used_columns = (df.columns.get_level_values("network")
                            .astype(int)
                            .isin(used_networks))
  df = df.loc[:, used_columns]
  
  # Compute the correlation matrix and average over networks
  corr_df = df.corr().groupby(level="network").mean()
  corr_df.index = corr_df.index.astype(int)
  corr_df = corr_df.sort_index().T
  
  # Set up the matplotlib figure
  f, ax = plt.subplots(figsize=(11, 6))
  
  # Draw a violinplot with a narrower bandwidth than the default
  sns.violinplot(data=corr_df, palette="Set3", bw=.2, cut=1, linewidth=1)
  
  # Finalize the figure
  ax.set(ylim=(-.7, 1.05))
  sns.despine(left=True, bottom=True)
  