old_contents: import numpy as np
  
  from bokeh.plotting import figure, output_file, show
  from bokeh.palettes import brewer
  
  # Define some categories
  categories = [
      'ousia', 'poson', 'poion', 'pros ti', 'pou',
      'pote', 'keisthai', 'echein', 'poiein', 'paschein',
  ]
  
  # Create data
  N = 10
  data = { cat : np.random.randint(10, 100, size=N) for cat in categories }
  
  # Define a little function to stack series together to make polygons. Soon
  # this will be built into Bokeh.
  def stacked(data, categories):
      ys = []
      last = np.zeros(len(list(data.values())[0]))
      for cat in categories:
          next = last + data[cat]
          ys.append(np.hstack((last[::-1], next)))
          last = next
      return ys
  
  # Get the y coordinates of the stacked data
  ys = stacked(data, categories)
  
  # The x coordinates for each polygon are simply the series concatenated
  # with its reverse.
  xs = [np.hstack((categories[::-1], categories))] * len(ys)
  
  # Pick out a color palette
  colors = brewer["Spectral"][len(ys)]
  
  # EXERCISE: output static HTML file
  
  # create a figure
  p = figure(title="Categories of Brewering", background_fill="lightgrey",
             tools="resize,reset,save", x_range=categories, y_range=[0, 800])
  
  # EXERCISE: play around with parameters like:
  #   - line_color
  #   - line_alpha
  #   - line_width
  #   - line_dash   (e.g., [2,4])
  #   - fill_color
  #   - fill_alpha
  
  # EXERCISE: configure all of the following plot properties
  p.ygrid.grid_line_color =
  p.ygrid.grid_line_width =
  p.axis.major_label_text_font_size =
  p.axis.major_label_text_font_style =
  p.axis.major_label_standoff =               # distance of tick labels from ticks
  p.axis.axis_line_color =                    # color, or None, to suppress the line
  p.xaxis.major_label_orientation =           # radians, "horizontal", "vertical", "normal"
  p.xaxis.major_tick_in =                     # distance ticks extends into the plot
  p.xaxis.major_tick_out =                    # and distance they extend out
  p.xaxis.major_tick_line_color =
  
  show(p)
  
new_contents: import numpy as np
  
  from bokeh.plotting import figure, output_file, show
  from bokeh.palettes import brewer
  
  # Define some categories
  categories = [
      'ousia', 'poson', 'poion', 'pros ti', 'pou',
      'pote', 'keisthai', 'echein', 'poiein', 'paschein',
  ]
  
  # Create data
  N = 10
  data = { cat : np.random.randint(10, 100, size=N) for cat in categories }
  
  # Define a little function to stack series together to make polygons. Soon
  # this will be built into Bokeh.
  def stacked(data, categories):
      ys = []
      last = np.zeros(len(list(data.values())[0]))
      for cat in categories:
          next = last + data[cat]
          ys.append(np.hstack((last[::-1], next)))
          last = next
      return ys
  
  # Get the y coordinates of the stacked data
  ys = stacked(data, categories)
  
  # The x coordinates for each polygon are simply the series concatenated
  # with its reverse.
  xs = [np.hstack((categories[::-1], categories))] * len(ys)
  
  # Pick out a color palette
  colors = brewer["Spectral"][len(ys)]
  
  # EXERCISE: output static HTML file
  
  # create a figure
  p = figure(title="Categories of Brewering", background_fill="lightgrey",
             tools="resize,reset,save", x_range=categories, y_range=[0, 800])
  
  # EXERCISE: play around with parameters like:
  #   - line_color
  #   - line_alpha
  #   - line_width
  #   - line_dash   (e.g., [2,4])
  #   - fill_color
  #   - fill_alpha
  
  # EXERCISE: configure all of the following plot properties
  p.ygrid.grid_line_color =
  p.ygrid.grid_line_width =
  p.axis.major_label_text_font_size =
  p.axis.major_label_text_font_style =
  p.axis.major_label_standoff =               # distance of tick labels from ticks
  p.axis.axis_line_color =                    # color, or None, to suppress the line
  p.xaxis.major_label_orientation =           # "horizontal", "vertical" or float value in radians
  p.xaxis.major_tick_in =                     # distance ticks extends into the plot
  p.xaxis.major_tick_out =                    # and distance they extend out
  p.xaxis.major_tick_line_color =
  
  show(p)
  
subject: Fix docs in styling exercise.