class_docstr: Main class producing plots. Each create_*() method reads group data from base_path and creates a plot at the
  save_path. create_all_plots() runs all these functions at once.
class_docstr_tok: ["Main","class","producing","plots",".","Each","create_","*","(",")","method","reads","group","data","from","base_path","and","creates","a","plot","at","the","save_path",".","create_all_plots","(",")","runs","all","these","functions","at","once","."]
docstr: Reads and parses group tables. Uses _tables_cache to avoid reprocessing the same table multiple times.
docstr_tok: ["Reads","and","parses","group","tables",".","Uses","_tables_cache","to","avoid","reprocessing","the","same","table","multiple","times","."]
code: def get_group_tables(self, group_name: str) -> Dict[str, Table]:
      """Reads and parses group tables. Uses _tables_cache to avoid reprocessing the same table multiple times."""
      if group_name in self._tables_cache:
          return self._tables_cache[group_name]
      with open(
          os.path.join(self.base_path, "groups", f"{group_name}.json")
      ) as fp:
          tables = json.load(fp)
  
      name_to_table: Dict[str, Table] = {}
      for table in tables:
          name_to_table[table["title"]] = parse_table(table)
  
      return name_to_table
  
imports: import argparse
  from collections import defaultdict
  from dataclasses import dataclass
  from datetime import date
  import json
  import os
  from typing import List, Dict, Optional, Any, Callable, Union, Mapping, Tuple, Set
  import colorcet
  import matplotlib
  import matplotlib.pyplot
  import numpy
  from scipy.stats import pearsonr
  import seaborn
  from helm.common.hierarchical_logger import hlog
  from helm.benchmark.presentation.schema import read_schema
  from helm.benchmark.presentation.summarize import AGGREGATE_WIN_RATE_COLUMN
label_desc: Use image node_id 2 for calling the Plotter obj's underlying member method code with example usage: obj.get_group_tables(group_name) and returns: name_to_table, self