code: def plot_perf_stats(returns, factor_returns, ax=None):
      
  
      if ax is None:
          ax = plt.gca()
  
      bootstrap_values = timeseries.perf_stats_bootstrap(returns,
                                                         factor_returns,
                                                         return_stats=False)
      bootstrap_values = bootstrap_values.drop('Kurtosis', axis='columns')
  
      sns.boxplot(data=bootstrap_values, orient='h', ax=ax)
  
      return ax
docs: Create box plot of some performance metrics of the strategy.
      The width of the box whiskers is determined by a bootstrap.
  
      Parameters
      ----------
      returns : pd.Series
          Daily returns of the strategy, noncumulative.
           - See full explanation in tears.create_full_tear_sheet.
      factor_returns : pd.Series
          Daily noncumulative returns of the benchmark factor to which betas are
          computed. Usually a benchmark such as market returns.
           - This is in the same style as returns.
      ax : matplotlib.Axes, optional
          Axes upon which to plot.
  
      Returns
      -------
      ax : matplotlib.Axes
          The axes that were plotted on.