Legend colors in Matplotlib table function?

Question

Does anyone know if it's possible to take the standard color boxes in the legend function in Matplotlib, and put those boxes in the rows of a table?

For example, look at this chart:

http://www.winplanet.com/img/screenshots/excel-datatable.gif

In the table at the bottom, you will see the small colored boxes next to the row items.

Is that possible to do with Matplotlib?

Answer 1

Sort of, but I'm not sure if you can make it so you can also resize the window (except before all the plotting).

I adapted the 'table' example from http://matplotlib.sourceforge.net/users/screenshots.html. It uses a separate axis that spans the whole figure and adds custom rectangle patches in the right spot. The right spot is simply what trial and error defines the right spot to be.

#!/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]]


figure(1)
clf()
ax = 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,
                  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')

ax2 = axes([0,0,1,1], frameon=False)
ax2.xaxis.set_visible(False)
ax2.yaxis.set_visible(False)

for ind, k in enumerate(colours):
    rect = matplotlib.patches.Rectangle((.07, -.0278*ind+.15), .015, .015, fill=True, fc = k, ec = '.0')
    ax2.add_patch(rect)                     

show()