code: def parse_table(raw_table: Dict[str, Any]) -> Table:
      """Convert raw table dict to a Table. Ignores strongly contaminated table entries."""
  
      def get_cell_values(cells: List[dict]) -> List[Any]:
          values = []
          for cell in cells:
              value = cell["value"] if "value" in cell else np.nan
              if (
                  "contamination_level" in cell
                  and cell["contamination_level"] == "strong"
              ):
                  value = np.nan
              values.append(value)
          return values
  
      adapters: Optional[List[str]] = None
      columns: List[Column] = []
      mean_win_rates: Optional[np.ndarray] = None
      for column_index, (header_cell, *column_cells) in enumerate(
          zip(raw_table["header"], *raw_table["rows"])
      ):
          cell_values = get_cell_values(column_cells)
          if column_index == 0:
              adapters = cell_values
          elif (
              column_index == AGGREGATE_WIN_RATE_COLUMN
              and "win rate" in header_cell["value"]
          ):
              mean_win_rates = np.array(cell_values)
          else:
              assert "metadata" in header_cell
              name = header_cell["value"]
              group = header_cell["metadata"]["run_group"]
              metric = header_cell["metadata"]["metric"]
              lower_is_better = (
                  header_cell["lower_is_better"]
                  if "lower_is_better" in header_cell
                  else None
              )
              columns.append(
                  Column(
                      name,
                      group,
                      metric,
                      np.array(cell_values),
                      lower_is_better,
                  )
              )
      assert adapters is not None
  
      return Table(adapters, columns, mean_win_rates)
  
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 1 for calling a global function with example usage: parse_table(raw_table) and returns: Table, values