code: def vertical(values, labels=None, sort=True, error=None, ax=None):
      """Plots vertical bars given a list of values
  
      Examples
      --------
      >>> import matplotlib.pyplot as plt
      >>> import numpy as np
      >>> from sklearn_evaluation.plot.matplotlib import bar
      >>> values = np.arange(10)
      >>> ax = bar.vertical(values)
  
      """
      if sort:
          idx_sorted = np.argsort(values)[::-1]
          values = values[idx_sorted]
  
          if labels is not None:
              labels = labels[idx_sorted]
  
      if ax is None:
          ax = plt.gca()
  
      x_pos = np.arange(len(values))
  
      if error is None:
          ax.bar(x_pos, values)
      else:
          ax.bar(x_pos, values, yerr=error)
  
      ax.set_xticks(x_pos)
      ax.set_xticklabels(x_pos if labels is None else labels)
      ax.set_xlim([-1, len(values)])
      ax.grid(axis="y")
      # ax.figure.tight_layout()
  
      return ax
  
file_path: sklearn-evaluation/src/sklearn_evaluation/plot/matplotlib/bar.py
imports: import numpy
  import matplotlib.pyplot
  from sklearn_evaluation.plot.matplotlib.data_grid import DataGrid
  from sklearn_evaluation.plot.util import set_default_ax
label_desc: Use image node_id 3 for calling a global function with example usage: vertical(values, labels, sort, error, ax) and returns: ax