Here is a snippet that might get you started:

import numpy as np

from matplotlib import pyplot as plt

from matplotlib import cm

import mpl_toolkits.mplot3d as plt3

data = np.random.random((8,8))**4

cmap = cm.RdBu

fig = plt.figure()

ax = plt3.Axes3D(fig)

d = 0.1

w, h = data.shape

for x in range(w):

for y in range(h):

ax.bar3d([x+d], [y+d], [0], 1-d, 1-d, data[x,y], cmap(data[x,y]))

ax.set_zlim3d((0, 1))

plt.show()

Obviously, you should replace data with the actual data you want to

plot (maybe numpy can help with the histogramming), and use an

appropriate cmap for your data. Note that in this case the entire box

is a single color, not shaded up the side as in the example you

referenced; I actually like it this way but I also don't know how one

would do the shading in matplotlib. I'll admit it's rather silly to

have to create all these boxes individually, but that's the only way I

could see to color each box according to its height. The variable d

just puts gaps between boxes; you could set this to zero to make the

boxes adjacent.

I haven't figured out how to properly set the tick labels on the x and

y axis in a 3d plot like this. Also, there are often some z-order

errors with boxes occluding each other when they shouldn't. I don't

know the details of how these things work internally; maybe some

experts could weigh in here.

Cheers,

Matthew

## ···

On Thu, Oct 1, 2009 at 3:29 PM, Ernest Adrogué <eadrogue@...361...> wrote:

Hello all,

What is the best way to plot a 2d histogram?

(Note that a 2d histogram is a histogram of a bivariate variable,

so it's got to be a 3d plot.)

Ideally, it should look somewhat like this:

http://www.desy.de/~mraue/public/rootTutorial/v0.2/histogram02.gif

For now, I have tried to do surface plots, one for each "bin",

but this way you only get the tops of a series of imaginary columns

and it looks a bit namby-pamby if you know what I mean.

Any idea will be appreciated.

--

Ernest

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