正文共3425个字，9张图，预计阅读时间9分钟。

# -*- coding=utf-8 -*-

from matplotlib import pyplot as plt

from sklearn.datasets

import load_iris

import numpy as np

import itertools

01

画散点图

plt.scatter(x,y) plt.title("Web traffic") plt.xlabel("Time") plt.ylabel("Hits/hour") plt.xticks([w*7*24 for w in range(10)],['week %i' %w for w in range(10)]) plt.autoscale(tight=True) plt.grid()##plt.show()

## 多项式拟合fp2 = np.polyfit(x,y,3) f2 = np.poly1d(fp2) fx = np.linspace(0,x[-1],1000) plt.plot(fx,f2(fx),linewidth=4,color='g')## f2.order: 函数的阶数plt.legend(["d=%i" % f2.order],loc="upper right") plt.show()

02

画多个子图

# -*- coding=utf-8 -*-from matplotlib import pyplot as pltfrom sklearn.datasets import load_irisimport numpy as npimport itertools data = load_iris()#print(data.data)#print(data.feature_names)#print(data.target)features = data['data'] feature_names = data['feature_names'] target = data['target'] labels = data['target_names'][data['target']] print(data.data) print(data.feature_names)

feature_names_2 = []#排列组合for i in range(1,len(feature_names)+1):    iter = itertools.combinations(feature_names,i)    feature_names_2.append(list(iter))     print(len(feature_names_2[1]))for i in feature_names_2[1]:    print(i)

plt.figure(1)for i,k in enumerate(feature_names_2[1]):    index1 = feature_names.index(k[0])    index2 = feature_names.index(k[1])    plt.subplot(2,3,1+i)    for t,marker,c in zip(range(3),">ox","rgb"):                plt.scatter(features[target==t,index1],features[target==t,index2],marker=marker,c=c)        plt.xlabel(k[0])        plt.ylabel(k[1])        plt.xticks([])        plt.yticks([])        plt.autoscale()        plt.tight_layout()       plt.show()

03

画水平线和垂直线

plt.figure(2)for t,marker,c in zip(range(3),">ox","rgb"):            plt.scatter(features[target==t,3],features[target==t,2],marker=marker,c=c)    plt.xlabel(feature_names[3])    plt.ylabel(feature_names[2])    # plt.xticks([])    # plt.yticks([])    plt.autoscale()     plt.vlines(1.6, 0, 8, colors = "c",linewidth=4,linestyles = "dashed") plt.hlines(2.5, 0, 2.5, colors = "y",linewidth=4,linestyles = "dashed") plt.show()

04

动态画图

plt.axis([0, 100, 0, 1]) plt.ion()for i in range(100):    y = np.random.random()    plt.autoscale()    plt.scatter(i, y)    plt.pause(0.01)