Python+matplotlib+numpy绘图实例 Python+matplotlib+numpy实现在不同平面的二维条形图

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np

# Fixing random state for reproducibility
np.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()