python matplotlib画图实例代码分享

import matplotlib.pyplot as plt 
import numpy as np 

t = np.arange(0.0,2.0,0.01)#x轴上的点，0到2之间以0.01为间隔 
s = np.sin(2*np.pi*t)#y轴为正弦 
plt.plot(t,s)#画图 
 
plt.xlabel('time (s)')#x轴标签 
plt.ylabel('voltage (mV)')#y轴标签 
plt.title('About as simple as it gets,folks')#图的标签 
plt.grid(True)#产生网格 
plt.savefig("test.png")#保存图像 
plt.show()#显示图像 

x1 = np.linspace(0.0,5.0)#画图一 
x2 = np.linspace(0.0,2.0)#画图二 
y1 = np.cos(2 * np.pi * x1) * np.exp(-x1) 
y2 = np.cos(2 * np.pi * x2) 
 
plt.subplot(2,1,1)#面板设置成2行1列，并取第一个（顺时针编号） 
plt.plot(x1,y1,'yo-')#画图，染色 
plt.title('A tale of 2 subplots') 
plt.ylabel('Damped oscillation') 
 
plt.subplot(2,2)#面板设置成2行1列，并取第二个（顺时针编号） 
plt.plot(x2,y2,'r.-')#画图，染色 
plt.xlabel('time (s)') 
plt.ylabel('Undamped') 
 
plt.show() 

# -*- coding:utf-8 -*- 
import numpy as np 
import matplotlib.mlab as mlab 
import matplotlib.pyplot as plt 
 
mu = 100 # 正态分布的均值 
sigma = 15 # 标准差 
x = mu + sigma * np.random.randn(10000)#在均值周围产生符合正态分布的x值 
 
num_bins = 50 
n,bins,patches = plt.hist(x,num_bins,normed=1,facecolor='green',alpha=0.5) 
#直方图函数，x为x轴的值，normed=1表示为概率密度，即和为一，绿色方块，色深参数0.5.返回n个概率，直方块左边线的x值，及各个方块对象 
y = mlab.normpdf(bins,mu,sigma)#画一条逼近的曲线 
plt.plot(bins,y,'r--') 
plt.xlabel('Smarts') 
plt.ylabel('Probability') 
plt.title(r'Histogram of IQ: $mu=100$,$sigma=15$')#中文标题 u'xxx' 
 
plt.subplots_adjust(left=0.15)#左边距 
plt.show() 

#!/usr/bin/env python 
# encoding: utf-8 
 
import matplotlib.pyplot as plt 
import numpy as np 
from mpl_toolkits.mplot3d import Axes3D 
 
x_list = [[3,3,2],[4,1],[1,2,3],[2,2]] 
fig = plt.figure() 
ax = fig.gca(projection='3d') 
for x in x_list: 
  ax.scatter(x[0],x[1],x[2],c='r') 
plt.show()

from mpl_toolkits.mplot3d.axes3d import Axes3D 
from matplotlib import cm 
import matplotlib.pyplot as plt 
import numpy as np 
  
fig = plt.figure() 
ax = fig.add_subplot(1,projection='3d') 
X=np.arange(1,10,1) 
Y=np.arange(1,1) 
X,Y = np.meshgrid(X,Y) 
Z = 3*X+2*Y+30 
surf = ax.plot_surface(X,Y,Z,rstride=1,cstride=1,cmap=cm.jet,linewidth=0,antialiased=True) 
ax.set_zlim3d(0,100) 
fig.colorbar(surf,shrink=0.5,aspect=5) 
plt.show()  

from mpl_toolkits.mplot3d import Axes3D 
from matplotlib import cm 
from matplotlib.ticker import LinearLocator,FormatStrFormatter 
import matplotlib.pyplot as plt 
import numpy as np 
 
fig = plt.figure() 
ax = fig.gca(projection='3d') 
X = np.arange(-5,5,0.1) 
Y = np.arange(-5,0.1) 
X,Y) 
R = np.sqrt(X**2 + Y**2) 
Z = np.sin(R) 
surf = ax.plot_surface(X,cmap=cm.coolwarm,antialiased=False) 
#画表面,x,z坐标， 横向步长，纵向步长，颜色，线宽，是否渐变 
ax.set_zlim(-1.01,1.01)#坐标系的下边界和上边界 
 
ax.zaxis.set_major_locator(LinearLocator(10))#设置Z轴标度 
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))#Z轴精度 
fig.colorbar(surf,aspect=5)#shrink颜色条伸缩比例（0-1），aspect颜色条宽度（反比例，数值越大宽度越窄） 
 
plt.show() 

# -*- coding: utf-8 -*- 
import matplotlib.pyplot as plt 
 
labels = 'Frogs','Hogs','Dogs','Logs'#设置标签 
sizes = [15,30,45,10]#占比，和为100 
colors = ['yellowgreen','gold','lightskyblue','lightcoral']#颜色 
explode = (0,0.1,0) #展开第二个扇形，即Hogs，间距为0.1 
 
plt.pie(sizes,explode=explode,labels=labels,colors=colors,autopct='%1.1f%%',shadow=True,startangle=90)#startangle控制饼状图的旋转方向 
plt.axis('equal')#保证饼状图是正圆，否则会有一点角度偏斜 
 
fig = plt.figure() 
ax = fig.gca() 
 
import numpy as np 
 
ax.pie(np.random.random(4),startangle=90,radius=0.25,center=(0,0),frame=True) 
ax.pie(np.random.random(4),center=(1,1),frame=True) 
 
ax.set_xticks([0,1])#设置位置 
ax.set_yticks([0,1]) 
ax.set_xticklabels(["Sunny","Cloudy"])#设置标签 
ax.set_yticklabels(["Dry","Rainy"]) 
ax.set_xlim((-0.5,1.5)) 
ax.set_ylim((-0.5,1.5)) 
 
ax.set_aspect('equal') 
plt.show()