python - matplotlib - Create a multiline graph with results summary underneath

From http://matplotlib.org/users/screenshots.html#table-demo

#!/usr/bin/env python
import matplotlib

from pylab import *
from matplotlib.colors import colorConverter


#Some simple functions to generate colours.
def pastel(colour, weight=2.4):
    """ Convert colour into a nice pastel shade"""
    rgb = asarray(colorConverter.to_rgb(colour))
    # scale colour
    maxc = max(rgb)
    if maxc < 1.0 and maxc > 0:
        # scale colour
        scale = 1.0 / maxc
        rgb = rgb * scale
    # now decrease saturation
    total = sum(rgb)
    slack = 0
    for x in rgb:
        slack += 1.0 - x

    # want to increase weight from total to weight
    # pick x s.t.  slack * x == weight - total
    # x = (weight - total) / slack
    x = (weight - total) / slack

    rgb = [c + (x * (1.0-c)) for c in rgb]

    return rgb

def get_colours(n):
    """ Return n pastel colours. """
    base = asarray([[1,0,0], [0,1,0], [0,0,1]])

    if n <= 3:
        return base[0:n]

    # how many new colours to we need to insert between
    # red and green and between green and blue?
    needed = (((n - 3) + 1) / 2, (n - 3) / 2)

    colours = []
    for start in (0, 1):
        for x in linspace(0, 1, needed[start]+2):
            colours.append((base[start] * (1.0 - x)) +
                           (base[start+1] * x))

    return [pastel(c) for c in colours[0:n]]



axes([0.2, 0.2, 0.7, 0.6])   # leave room below the axes for the table

data = [[  66386,  174296,   75131,  577908,   32015],
        [  58230,  381139,   78045,   99308,  160454],
        [  89135,   80552,  152558,  497981,  603535],
        [  78415,   81858,  150656,  193263,   69638],
        [ 139361,  331509,  343164,  781380,   52269]]

colLabels = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rowLabels = ['%d year' % x for x in (100, 50, 20, 10, 5)]

# Get some pastel shades for the colours
colours = get_colours(len(colLabels))
colours.reverse()
rows = len(data)

ind = arange(len(colLabels)) + 0.3  # the x locations for the groups
cellText = []
width = 0.4     # the width of the bars
yoff = array([0.0] * len(colLabels)) # the bottom values for stacked bar chart
for row in xrange(rows):
    bar(ind, data[row], width, bottom=yoff, color=colours[row])
    yoff = yoff + data[row]
    cellText.append(['%1.1f' % (x/1000.0) for x in yoff])

# Add a table at the bottom of the axes
colours.reverse()
cellText.reverse()
the_table = table(cellText=cellText,
                  rowLabels=rowLabels, rowColours=colours,
                  colLabels=colLabels,
                  loc='bottom')
ylabel("Loss $1000's")
vals = arange(0, 2500, 500)
yticks(vals*1000, ['%d' % val for val in vals])
xticks([])
title('Loss by Disaster')

show()

Edit: This example can be simplified by using the default matplotlib color cycle (blue, red, green, ....) and line plots as follows:

import numpy as np
import matplotlib.pyplot as plt

#Create a figure and axes with room for the table
fig = plt.figure()
ax = plt.axes([0.2, 0.2, 0.7, 0.6])

#Create labels for the rows and columns as tuples
colLabels = ('36', '40', '44', '48', '149', '153', '157', '161', '165')
rowLabels = ('UDL DL', 'UDP UL', 'TCP DL', 'TCP UL')

#Table data as a numpy array
tableData = np.array([[  36.7128,  37.684,   38.283,  48.425,   32.839, 36.424, 34.440, 31.642, 35.710],
        [  36.7128,  37.684,   38.283,  48.425,   32.839, 36.424, 34.440, 31.642, 35.710],
        [  36.7128,  37.684,   38.283,  48.425,   32.839, 36.424, 34.440, 31.642, 35.710],
        [  36.7128,  37.684,   38.283,  48.425,   32.839, 36.424, 34.440, 31.642, 35.710]])

#Get the current color cycle as a list, then reset the cycle to be at the beginning
colors = []     
while True:
    colors.append(ax._get_lines.color_cycle.next())
    if colors[0] == colors[-1] and len(colors)>1:
        colors.pop(-1)
        break

for i in xrange(len(colors)-1):
    ax._get_lines.color_cycle.next()

#Show the table
table = plt.table(cellText=tableData,
                  rowLabels=rowLabels, rowColours=colors,
                  colLabels=colLabels,
                  loc='bottom')

#Make some line plots
x = np.linspace(0,10,100)                  
ax.plot(x,np.sin(x))
ax.plot(x,-1*np.sin(x))
ax.plot(x,np.cos(x))
ax.plot(x,-1*np.cos(x))

#Turn off x-axis ticks and show the plot              
plt.xticks([])
plt.show()