code: def _load_benchmark_data(result_dir=None):
      if result_dir is None:
          result_dir = get_last_result_dir(BASE_FILE_NAME)
  
      cols = [
          "time",
          "iterations",
          "n_threads",
          "coeffs",
          "exectuable",
          "build",
      ]
  
      df = pd.DataFrame(columns=cols)
      for result_file in [
          f for f in os.listdir(result_dir) if f.endswith("tsv")
      ]:
          result_path = os.path.join(result_dir, result_file)
          local_df = pd.read_csv(
              result_path, sep="\t", names=cols[:-1], index_col=False
          )
          local_df[cols[-1]] = extract_build_from_name(result_file)
          df = df.append(local_df)
  
      for num_col in [
          col for col in cols if col not in ["exectuable", "build"]
      ]:
          df[num_col] = pd.to_numeric(df[num_col])
  
      return df, result_dir
  
imports: import os
  import matplotlib.pyplot
  import numpy
  import pandas
  from tools.benchmark.benchmark_util import iter_executables, run_benchmark, extract_build_from_name, default_result_dir, get_last_result_dir
label_desc: Use image node_id 2 for calling a global function with example usage: _load_benchmark_data(result_dir) and returns: df,  result_dir