code: def _tabulate(results, metrics, formats):
      """Prints results by metric and format
  
      Uses the last ([-1]) value of other fields
      """
      column_width = max(max(len(k) for k in formats) + 1, 8)
      first_width = max(len(k) for k in metrics)
      head_fmt = "{:<{fw}s}" + "{:>{cw}s}" * len(formats)
      row_fmt = "{:<{fw}s}" + "{:>{cw}.3f}" * len(formats)
      print(
          head_fmt.format(
              "Metric", *formats, cw=column_width, fw=first_width
          )
      )
      for metric, row in zip(metrics, results[:, :, -1, -1, -1]):
          print(
              row_fmt.format(
                  metric, *row, cw=column_width, fw=first_width
              )
          )
  
file_path: scikit-learn/benchmarks/bench_multilabel_metrics.py
imports: import argparse
  import itertools
  import sys
  from functools import partial
  from timeit import timeit
  import matplotlib.pyplot
  import numpy
  import scipy.sparse
  from sklearn.datasets import make_multilabel_classification
  from sklearn.metrics import accuracy_score, f1_score, hamming_loss, jaccard_similarity_score
  from sklearn.utils._testing import ignore_warnings
label_desc: Use image node_id 2 for calling a global function with example usage: _tabulate(results, metrics, formats) without return types