docs: def quantiles(xs, qs=None, step=25, width=None, cellspacing=3):
      '''
      Use stats.quantiles to get quantile-value pairs, and then print them to fit.
      >>> import numpy as np
      >>> quantiles(np.random.normal(size=10000), qs=[0, 5, 50, 95, 100])
       0% < -3.670    5% < -1.675   50% < -0.002   95% < 1.6500   100% < 3.4697
      (Or something like that)
      '''
  
      if width is None:
          width = terminal.width()
  
      qs_values = stats.quantiles(xs, qs=qs, step=step)
  
      ncells = len(qs_values)
      cellspacing_total = (ncells - 1) * cellspacing
      cell_width = int((width - cellspacing_total) / ncells)
  
      cells = ['%2d%% < %s' % (q, format_float(value, cell_width - 6)) for q, value in qs_values]
  
      print (' '*cellspacing).join(cells)