下面是解决方案，那些想要使用contourf或出于其他原因需要fill_between的人（就像在这种情况下，不规则的网格数据）。

import numpy as np
import matplotlib.pyplot as plt
from random import randint, sample
import matplotlib.colorbar as cbar

# from Numeric import asarray
%matplotlib inline

# The edges of 2d grid
# Some x column has varying rows of y (but always the same number of rows) 
# z array that corresponds a value in each xy cell

xedges = np.sort(sample(range(1, 9), 6))
yedges = np.array([np.sort(sample(range(1, 9), 6)) for i in range(5)])
z = np.random.random((5,5))

f, ax = plt.subplots(1, sharex=True, figsize=(8,8))
f.subplots_adjust(hspace=0)
ax.set_ylabel(r'y')
ax.set_xlabel(r'x')
ax.set_ylim(0,10)
ax.set_xlim(0,10)

c = ['r','g','b','y','m']

normal = plt.Normalize(z.min(), z.max())
cmap = plt.cm.jet(normal(z))

# plot showing bins, coloured arbitrarily.
# I want each cell coloured according to z.
for i in range(len(xedges)-1):
    for j in range(len(yedges)):
        ax.vlines(xedges[i],yedges[i][j],yedges[i][j+1],linestyle='-')
        ax.hlines(yedges[i][j],xedges[i],xedges[i+1],linestyle='-')
        ax.vlines(xedges[i+1],yedges[i][j],yedges[i][j+1],linestyle='-')
        ax.hlines(yedges[i][j+1],xedges[i],xedges[i+1],linestyle='-')

        ax.fill_between([xedges[i],xedges[i+1]],yedges[i][j],yedges[i][j+1],facecolor=cmap[i][j][:])

cax, _ = cbar.make_axes(ax) 
cb2 = cbar.ColorbarBase(cax, cmap=plt.cm.jet,norm=normal)

这给

我觉得你应该用contourf
http://matplotlib.org/examples/pylab_examples/contourf_demo.html
这将以x作为某个因变量，产生y = y(x)和z = z(x)。看起来你的z并不依赖于y，但是contourf仍然可以处理这个问题。
举个简单的例子：

import pylab as plt
x = plt.linspace(0,2,100)
y = plt.linspace(0,10,100)

z = [[plt.sinc(i) for i in x] for j in y]

CS = plt.contourf(x, y, z, 20, # \[-1, -0.1, 0, 0.1\],
                        cmap=plt.cm.rainbow)
plt.colorbar(CS)
plt.plot(x,2+plt.sin(y), "--k")

有许多变化，但希望这捕获的元素，你正在寻找