Python+matplotlib+numpy实现在不同平面的二维条形图

from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as pltimport numpy as np# Fixing random state for reproducibilitynp.random.seed(19680801)fig = plt.figure()ax = fig.add_subplot(111, projection='3d')colors = ['r', 'g', 'b', 'y']yticks = [3, 2, 1, 0]for c, k in zip(colors, yticks):  # Generate the random data for the y=k 'layer'.  xs = np.arange(20)  ys = np.random.rand(20)  # You can provide either a single color or an array with the same length as  # xs and ys. To demonstrate this, we color the first bar of each set cyan.  cs = [c] * len(xs)  cs[0] = 'c'  # Plot the bar graph given by xs and ys on the plane y=k with 80% opacity.  ax.bar(xs, ys, zs=k, zdir='y', color=cs, alpha=0.8)ax.set_xlabel('X')ax.set_ylabel('Y')ax.set_zlabel('Z')# On the y axis let's only label the discrete values that we have data for.ax.set_yticks(yticks)plt.show()