code: def plot_summary_axes(graph: BELGraph, lax, rax, logx=True):
      
      ntc = count_functions(graph)
      etc = count_relations(graph)
  
      df = pd.DataFrame.from_dict(dict(ntc), orient='index')
      df_ec = pd.DataFrame.from_dict(dict(etc), orient='index')
  
      df.sort_values(0, ascending=True).plot(kind='barh', logx=logx, ax=lax)
      lax.set_title('Number of nodes: {}'.format(graph.number_of_nodes()))
  
      df_ec.sort_values(0, ascending=True).plot(kind='barh', logx=logx, ax=rax)
      rax.set_title('Number of edges: {}'.format(graph.number_of_edges()))
docs: Plots your graph summary statistics on the given axes.
  
      After, you should run :func:`plt.tight_layout` and you must run :func:`plt.show` to view.
  
      Shows:
      1. Count of nodes, grouped by function type
      2. Count of edges, grouped by relation type
  
      :param pybel.BELGraph graph: A BEL graph
      :param lax: An axis object from matplotlib
      :param rax: An axis object from matplotlib
  
      Example usage:
  
      >>> import matplotlib.pyplot as plt
      >>> from pybel import from_pickle
      >>> from pybel_tools.summary import plot_summary_axes
      >>> graph = from_pickle('~/dev/bms/aetionomy/parkinsons.gpickle')
      >>> fig, axes = plt.subplots(1, 2, figsize=(10, 4))
      >>> plot_summary_axes(graph, axes[0], axes[1])
      >>> plt.tight_layout()
      >>> plt.show()