Matplotlib 3D Scatter Plot with Colorbar

Question

Borrowing from the example on the Matplotlib documentation page and slightly modifying the code,

import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt  def randrange(n, vmin, vmax):     return (vmax-vmin)*np.random.rand(n) + vmin  fig = plt.figure() ax = fig.add_subplot(111, projection='3d') n = 100 for c, m, zl, zh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:     xs = randrange(n, 23, 32)     ys = randrange(n, 0, 100)     zs = randrange(n, zl, zh)     cs = randrange(n, 0, 100)     ax.scatter(xs, ys, zs, c=cs, marker=m) ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_zlabel('Z Label')  plt.show() 

Will give a 3D scatter plot with different colors for each point (random colors in this example). What's the correct way to add a colorbar to the figure, since adding in plt.colorbar() or ax.colorbar() doesn't seem to work.

Answer 1

This produces a colorbar (though possibly not the one you need):

Replace this line:

ax.scatter(xs, ys, zs, c=cs, marker=m) 

with

p = ax.scatter(xs, ys, zs, c=cs, marker=m) 

then use

fig.colorbar(p) 

near the end