old_contents: from collections import Counter
  from data_tools import plotting as dtp
  
  
  def display_graph(table):
      cnt = Counter()
      Row_list = []
      df = table[[item for item in table.columns if "label" in item]].drop_duplicates()
      for rows in df.itertuples():
          if len(Row_list) > 12:
              break
          if cnt[rows.output_label] < 3:
              # Create list for the current row
              my_list = list(rows)[1:]
  
              # append the list to the final list
              Row_list.append(my_list)
  
              cnt[rows.output_label] += 1
      G = dtp.build_explanitory_graph(Row_list)
      dtp.draw_explanitory_graph(G)
  
new_contents: from collections import Counter
  from data_tools import plotting as dtp
  
  
  def display_graph(table):
      cnt = Counter()
      Row_list = []
      label_dict = {}
      df = table[
          [item for item in table.columns if "label" in item or "type" in item]
      ].drop_duplicates()
      for rows in df.itertuples():
          if len(Row_list) > 12:
              break
          if cnt[rows.output_label] < 3:
              my_list = []
  
              for i in range(1, len(list(rows)), 2):
                  my_list.append(list(rows)[i])
                  label_dict[list(rows)[i]] = list(rows)[i + 1]
              # Create list for the current row
              # my_list = list(rows)[1:]
  
              # append the list to the final list
              Row_list.append(my_list)
  
              cnt[rows.output_label] += 1
      G = dtp.build_explanitory_graph(Row_list, node_id_to_label=label_dict)
      dtp.draw_explanitory_graph(G)
  
subject: add node color feature