python之可视化matplotlib

# -*- coding: utf-8 -*-

importnumpyasnp

importmatplotlib.pyplotasplt

importmatplotlib.datesasmdates

##########简单线型图

# plt.plot([1,3],[3,1])

# plt.show()

#########################################

################散点图

#不相关

# height=[161,170,182,175,173,165]

# weight=[50,58,80,70,69,55]

# plt.scatter(height,weight)

# plt.show()

############################

# N=1000

# x=np.random.randn(N)

# y1=np.random.randn(N)

# plt.scatter(x,y1)

# plt.show()

######################################股票价格指数

# open,close=np.loadtxt('000001.csv',delimiter=',',skiprows=1,usecols=(1,4),unpack=True)

# change=open-close

# yesterday=change[:-1]

# today=change[1:]

# plt.scatter(yesterday,today,s=500,c='r',marker='<',alpha=0.5)

# plt.show()

#########################################折线图

# x=np.linspace(-10,10,10)

# y=x**2

# plt.plot(x,y)

# plt.show()

####################################股票序列折线图

# date,open,close=np.loadtxt('000001.csv',delimiter=',',skiprows=1,converters={0:mdates.strpdate2num('%m/%d/%Y')},usecols=(0,1,4),unpack=True)

# plt.plot_date(date,open,linestyle='-',color='green',marker='<')

# plt.plot_date(date,close,linestyle='--',color='red',marker='<')

# plt.show()

#################################################条形图

#纵项条形图

# N=5

# y=[20,10,30,25,15]

# index=np.arange(N)

# pl=plt.bar(left=index,height=y,width=0.8,color='red')

# plt.show()

#横向条形图

# N=5

# y=[20,10,30,25,15]

# index=np.arange(N)

# #pl=plt.bar(left=0,bottom=index,height=0.5,width=y,color='red',orientation='horizontal')

# pl=plt.barh(left=0,bottom=index,width=y,height=0.5)

# plt.show()

########################################################双向并列图

# index=np.arange(4)

# sale_BJ=[52,55,63,53]

# sale_SH=[44,66,55,41]

# bar_width=0.3

# plt.bar(index,sale_BJ,bar_width,color='b')

# plt.bar(index+bar_width,sale_SH,bar_width,color='red')

# plt.show()

#######################################################################双向层叠图

# index=np.arange(4)

# sale_BJ=[52,55,63,53]

# sale_SH=[44,66,55,41]

# bar_width=0.3

# plt.bar(index,sale_BJ,bar_width,color='b')

# plt.bar(index,sale_SH,bar_width,color='r',bottom=sale_BJ)

# plt.show()

##################################################直方图

# mu=100

# sigma=20

# x=mu+sigma*np.random.randn(2000)

# #plt.hist(x,bins=50,color='red',normed=True)

# plt.hist(x,bins=10000,color='green',normed=False)

# plt.show()

###################################################33饼状图

# labels=['A','B','C','D']

# fracs=[15,30,45,10]

# plt.axes(aspect=1) #使得饼状图为圆形，而不为椭圆

# explod=[0,0,0.05,0]#突出某一重点

# plt.pie(x=fracs,labels=labels,autopct='%0.f%%',explode=explod,shadow=True)

# plt.show()0

#############################################箱形图

# np.random.seed(100)

# data=np.random.normal(size=1000,loc=0,scale=1)

# plt.boxplot(data,sym='o')

# plt.show()

##############四组箱线图

# np.random.seed(100)

# data=np.random.normal(size=(1000,4),loc=0,scale=1)

# labels=['A','B','C','D']

# plt.boxplot(data,sym='o',labels=labels)

# plt.show()

########################同时生成两张图

# fig1=plt.figure()

# ax1=fig1.add_subplot(111)

# ax1.plot([1,2,3],[3,2,1])

# fig2=plt.figure()

# ax2=fig2.add_subplot(111)

# ax2.plot([1,2,3],[1,2,3])

# plt.show()

###########################

x=np.arange(1,11,1)

y=x*x

plt.plot(x,x*2,label='Normal')

plt.plot(x,x*3,label='Fast')

plt.plot(x,x*4,label='Faster')

plt.legend(loc=3,ncol=2)   #图例

plt.show()