code: def plot_feature_importance_ranking(cls, feature_importance_ranking):
      plt.figure(figsize=(12, 8))
  
      features = np.array([a for a, _ in feature_importance_ranking])
      scores = np.array([b for _, b in feature_importance_ranking])
  
      ax = sns.barplot(
          x=scores,
          y=features,
          palette=sns.color_palette("Blues_d"),
          orient="h",
      )
      plt.autoscale(enable=True, axis="both", tight=True)
      plt.show()
  
file_path: contextual-ai/xai/plots/data_stats_notebook_plots.py
imports: from collections import Counter
  import matplotlib.pyplot
  import pandas
  import numpy
  import seaborn
  from IPython.display import display, Markdown
label_desc: Use image node_id 6 for calling the NotebookPlots obj's underlying member method code with example usage: obj.plot_feature_importance_ranking(cls, feature_importance_ranking) without return types