pycharm使用matplotlib绘图学习笔记「建议收藏」

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#encoding=utf-8
import numpy as np


def main():
    import matplotlib.pyplot as plt

    ##lesson1:画图
    # x = np.linspace(-1, 1, 50)
    # x=np.linspace(-np.pi,np.pi,256,endpoint=True)
    # c,s=np.cos(x),np.sin(x)
    # plt.figure(1)
    # plt.plot(x,c,color="blue",linewidth=1.0,linestyle="-",label="COS",alpha=0.5)
    # plt.plot(x,s,"r*",label="SIN")
    # plt.title("COS & SIN")
    # ##设置坐标轴
    # ax=plt.gca()
    # ax.spines["right"].set_color("none")
    # ax.spines["top"].set_color("none")
    # ax.spines["left"].set_position(("data",0))
    # ax.spines["bottom"].set_position(("data",0))
    # ax.xaxis.set_ticks_position("bottom")
    # ax.yaxis.set_ticks_position("left")
    # ##网格填充
    # plt.grid()
    # plt.fill_between(x,np.abs(x)<0.5,c,c>0.5,color="green",alpha=0.25)
    # ##注释
    # t=1
    # plt.plot([t,t],[0,np.cos(t)],"y",linewidth=3,linestyle="--")
    # plt.annotate("cos(1)",xy=(t,np.cos(1)),xycoords="data",xytext=(+10,+30),textcoords="offset points",arrowprops=dict(arrowstyle="->",connectionstyle="arc3,rad=.2"))
    #
    # plt.show()

    ##lesson2:数据分析常见图形
    ##散点图scatter
    # fig=plt.figure()
    # ax=fig.add_subplot(3,3,1)
    # n=128
    # X=np.random.normal(0,1,n)#随机数
    # Y=np.random.normal(0,1,n)#随机数
    # T=np.arctan2(Y,X)#上色
    # #plt.axes([0.025,0.025,0.95,0.95])#指定现实范围
    # #plt.scatter(X,Y,s=75,c=T,alpha=0.5)#画散点
    # ax.scatter(X, Y, s=75, c=T, alpha=0.5)  # 画散点
    # plt.xlim(-1.5,1.5),plt.xticks([])#X范围
    # plt.ylim(-1.5,1.5),plt.yticks([])#Y范围
    # plt.axis()
    # plt.title("scatter")
    # plt.xlabel("x")
    # plt.ylabel("y")
    # plt.show()

    # #bar柱状图
    # fig = plt.figure()
    # fig.add_subplot(332)
    # n=10
    # X=np.arange(n)
    # Y1=(1-X/float(n))*np.random.uniform(0.5,1.0,n)
    # Y2=(1-X/float(n))*np.random.uniform(0.5,1.0,n)
    #
    # plt.bar(X,+Y1,facecolor='#9999ff',edgecolor='white')
    # plt.bar(X,-Y2,facecolor='#ff9999',edgecolor='white')
    # for x,y in zip(X,Y1):
    #     plt.text(x+0.4,y+0.05,'%.2f'%y,ha='center',va='bottom')
    #
    # for x,y in zip(X,Y2):
    #     plt.text(x+0.4,-y-0.05,'%.2f'%y,ha='center',va='top')
    #
    # plt.show()

    # #pie饼状图
    # fig = plt.figure()
    # fig.add_subplot(333)
    # n=20
    # Z=np.ones(n)
    # Z[-1]*=2
    # plt.pie(Z,explode=Z*.05,colors=['%f'%(i/float(n)) for i in range(n)],
    #         labels=['%.2f'%(i/float(n)) for i in range(n)])
    # plt.gca().set_aspect('equal')
    # plt.xticks([]),plt.yticks([])
    # plt.show()

    # #polar极线图
    # fig = plt.figure()
    # fig.add_subplot(334,polar=True)
    # n=20
    # theta=np.arange(0.0,2*np.pi,2*np.pi/n)
    # radii=10*np.random.rand(n)
    # #plt.plot(theta,radii)
    # plt.polar(theta,radii)
    # plt.show()

    #heatmap热力图
    # fig=plt.figure()
    # fig.add_subplot(335)
    # from matplotlib import cm
    # data=np.random.rand(3,3)
    # cmap=cm.Blues
    # map=plt.imshow(data,interpolation='nearest',cmap=cmap,aspect='auto',vmin=0,vmax=1)
    # plt.show()

    # #3D图
    # fig=plt.figure()
    # ax=fig.add_subplot(336,projection="3d")
    # ax.scatter(1,1,3,s=100)
    # plt.show()

    # #hot map热图
    # fig=plt.figure()
    # fig.add_subplot(313)
    # def f(x,y):
    #     return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
    # n=256
    # x=np.linspace(-3,3,n)
    # y=np.linspace(-3,3,n)
    # X,Y=np.meshgrid(x,y)
    # plt.contourf(X,Y,f(X,Y),8,alpha=.75,cmap=plt.cm.hot)
    # plt.show()
    #
    # ##保存图片
    # plt.savefig("./data/fig.png")

if __name__ == '__main__':
    main()