直接看注释吧，知行合一！
# -*- coding: utf-8 -*- """ Created on Tue Mar 21 10:36:28 2017 罗干，同济大学图书馆 我爱婷婷和臭臭 @author: user """ #导入模块 from matplotlib import pyplot as plt import numpy as np #定义两个矩阵 A1=np.array([0,0]) B1=np.array(([2,0],[0,2])) #以 A1为均值，B1为协方差矩阵，生成正态分布的随机数 C1=np.random.multivariate_normal(A1,B1,10) C2=np.random.multivariate_normal(A1+0.2,B1+0.2,10) #画布的大小为长8cm高6cm plt.figure(figsize=(8,6)) #画图吧，s表示点点的大小，c就是color嘛，marker就是点点的形状哦o,x,*><^,都可以啦 #alpha,点点的亮度，label，标签啦 plt.scatter(C1[:,0],C1[:,1],s=30,c='red',marker='o',alpha=0.5,label='C1') plt.scatter(C2[:,0],C2[:,1],s=30,c='blue',marker='x',alpha=0.5,label='C2') #下面三行代码很简单啦 plt.title('basic scatter plot ') plt.xlabel('variables x') plt.ylabel('variables y') plt.legend(loc='upper right')#这个必须有，没有你试试看 plt.show()#这个可以没有 import matplotlib.pyplot as plt x_coords = [0.13, 0.22, 0.39, 0.59, 0.68, 0.74, 0.93] y_coords = [0.75, 0.34, 0.44, 0.52, 0.80, 0.25, 0.55] fig = plt.figure(figsize=(8,5)) plt.scatter(x_coords, y_coords, marker='s', s=50) for x, y in zip(x_coords, y_coords): plt.annotate( '(%s, %s)' %(x, y), xy=(x, y), xytext=(0, -10), textcoords='offset points', ha='center', va='top') plt.xlim([0,1]) plt.ylim([0,1]) plt.show() import numpy as np import matplotlib.pyplot as plt fig = plt.figure(figsize=(8,6)) # Generating a Gaussion dataset: # creating random vectors from the multivariate normal distribution # given mean and covariance mu_vec1 = np.array([0,0]) cov_mat1 = np.array([[1,0],[0,1]]) X = np.random.multivariate_normal(mu_vec1, cov_mat1, 500) R = X**2 R_sum = R.sum(axis=1) plt.scatter(X[:, 0], X[:, 1], color='gray', marker='o', s=32. * R_sum, edgecolor='black', alpha=0.5) plt.show()转载自斗大的熊猫
