54321
import matplotlib.pyplot as plt
labels = ['Class 1', 'Class 2', 'Class 3']
sizes=[30.521, 40.3, 50.536]
explode =[0.1, 0, 0]
colors = ['r','g','b]
plt.pie(sizes, explode = explode, labels = labels, colors= colors,autopct =%4.2f%%, shadow = False, startangle = 98)plt.show()
import matplotlib. pyplot as plt
import numpy as np
mu=100
sigma=20
#设置均#用于将x中的点分布在m 旁边，以mu为中x=mu+sigma*np. random. randn(20000)t bins 设置分组的个数100(显示有！p1t.hist(x, bins=100, color= green plt. show)
#条形图（bar）
import matplotlib.pyplot as plt
import numpy as np
y=[20, 10,30, 25, 15, 34, 22,11]x=np.arange(8) #0---7 plt. show()
plt. bar(x,height=y, color=' green',width=0.5)
import matplotlib.pyplot as plt
x= ['a',b,
y=[80,100,
p1 = plt.bar(x, height =y, width = 0.5)
plt.show()
import matplotlib.pyplot as plt
country = ['USA', 'China','Japan',
'Germany'GDP =[209328, 147228, 50487, 38030, 27110]plt.barh(country
GDP)
from matplotlib impont pyplot as plt
import numpy as np
a=np.array([1,2,3,4,5,12,13,14,15,19])plt.hist(a, bins= [0,5,10,15,201)plt.title("histogram")
plt.show()
# -*- coding:utf-8 一*一
import numpy as np
import matplotlib. pyplot as plt
plt.figure(1)
# 创建图表1
plt. figure(2)
# 创建图表2
ax1 = plt. subplot (211)# 在图表2中ax2 = plt. subplot(212)# 在图表2中x= np.linspace(0,3, 100)
for i in x:
plt.figure(1)
)# 选择图表1 plt.p1ot (x, np.exp(i*x/3))plt.sca(axl)
#选择图表2的子plt.sca(ax2) = 选择图表2的子图
plt.plot(x, np.sin(i*x))plt.plot(x, np.cos(i*x))plt.show()
#箱形图
import numpy as np
import matplotlib. pyplot as plt
np.random. seed(100)
data = np. random, normal(size = (1000, ), loc = 0, scale= 1)
#sym 调整好异常值的点的形状
#whis 默认是1.5,
通过调整它的竖直来设置异常值显示的数量，# 如果想显示尽可能多的异常值，whis设置很小，否则很大plt.boxplot (data, sym ="o
# plt. boxplot (data,
，whis = 1.5)
plt.show()
。whis = 0.01)
import matplotlib.pyplot as plt
import numpy as np
numberOfPoints=16
theta = np.linspace(0.0, 2*np.pi, numberofPoints)
r= 30 *np.random.rand(number0fPoints)
elt.polar(theta,r, linewidth =2, c ='g', marker ="o", mfc = "n", ms = 8)
plt.show()