python机器学习入门之matplotlib的使用（超详细，必看）

悠悠 2023-09-30 15:24 3阅读 0赞

matplotlib是python的一个基本2D绘图库 功能强大

**比较常用的是里面的pyplot子模块**

**常见函数有figure（）创建一个空白画布 add\_subplot()创建子图 title()设置标题**

**xlabel()设置x轴名称 ylabel（）设置y轴名称 legend()指定图例 show（）显示图形等等**

实例一如下

![67652be690ee42d6adff73c595644a4e.png][]

**代码如下**

import pandas as pd
    import numpy as np
    from pandas import Series
    from numpy import nan as NA
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    fig=plt.figure()
    
    ax1=fig.add_subplot(2,2,1)
    ax2=fig.add_subplot(2,2,2)
    ax3=fig.add_subplot(2,2,3)
    plt.show()

**2:在子图上绘制图形 如三角形 椭圆 矩形**

**![578adbcc15ab4a69b27a2ed2a76a7415.png][]**

**代码如下**

import pandas as pd
    import numpy as np
    from pandas import Series
    from numpy import nan as NA
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    ax=fig.add_subplot(1,1,1)
    rect=plt.Rectangle((0.2,0.75),0.4,0.15,color='r',alpha=0.3)
    cir=plt.Circle((0.7,0.2),0.15,color='b',alpha=0.3)
    pgon=plt.Polygon([[0.2,0.2],[0.35,0.25],[0.2,0.6]],color='g',alpha=0.9)
    ax.add_patch(rect)
    ax.add_patch(cir)
    ax.add_patch(pgon)
    plt.show()

**3：直线图的绘画**

![f767ba2645814990b6fe4a4dd64c5178.png][]

import pandas as pd
    import numpy as np
    from pandas import Series
    from numpy import nan as NA
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    a=np.arange(10)
    plt.xlabel('x')
    plt.ylabel('y')
    plt.plot(a,a*1.5,a,a*2.5,a,a*3.5,a,a*4.5)
    plt.legend(['1.5x','2.5x','3.5x','4.5x'])
    plt.title('simple lines')
    j=np.linspace(-10,10,100)
    k=np.sin(j)
    plt.plot(j,k,marker="o")
    plt.show()

**4：为series数据绘制图形**

![e7f7b3780e684faf9716295d76fe3406.png][]

import numpy as np
    from pandas import Series
    from numpy import nan as NA
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    s1=Series(np.random.randn(1000).cumsum())
    s2=Series(np.random.randn(1000).cumsum())
    plt.subplot(2,1,1)
    ax1=s1.plot(kind='line',label='S1',title="figures of Series",style='--')
    s2.plot(ax=ax1,kind='line',label='S2')
    plt.ylabel('value')
    plt.legend(loc=2)
    plt.subplot(2,1,2)
    s1[0:10].plot(kind='bar',grid=True,label='s1')
    plt.xlabel('index')
    plt.ylabel('value')
    plt.show()

**5：三维图形的绘画 虽说matplotlib主要用于二维图形绘制 但是三维的也可以画**

![809c9e431b2f486397512da3a181855b.png][]

import numpy as np
    from pandas import Series
    from numpy import nan as NA
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
    def randrange(n,randFloor,randceil):
        rnd=np.random.rand(n)
        return (randceil-randFloor)*rnd+randFloor
    plt.rcParams['font.sans-serif']=['SimHei']
    fig=plt.figure(figsize=(10,8))
    ax=fig.add_subplot(111,projection="3d")
    n=100
    for zmin,zmax,c,m,l in[(4,15,'r','o','低值'),(13,40,'g','*','高值')]:
        x=randrange(n,0,20)
        y=randrange(n,0,20)
        z=randrange(n,zmin,zmax)
        ax.scatter(x,y,z,c=c,marker=m,label=l,s=z*6)
    ax.set_xlabel("x-value")
    ax.set_ylabel("y-value")
    ax.set_zlabel("z-value")
    ax.set_title("高低值 3D散点图",alpha=0.6,size=15,weight='bold')
    ax.legend(loc="upper left")
    plt.show()

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[67652be690ee42d6adff73c595644a4e.png]: https://img-blog.csdnimg.cn/67652be690ee42d6adff73c595644a4e.png
[578adbcc15ab4a69b27a2ed2a76a7415.png]: https://img-blog.csdnimg.cn/578adbcc15ab4a69b27a2ed2a76a7415.png
[f767ba2645814990b6fe4a4dd64c5178.png]: https://img-blog.csdnimg.cn/f767ba2645814990b6fe4a4dd64c5178.png
[e7f7b3780e684faf9716295d76fe3406.png]: https://img-blog.csdnimg.cn/e7f7b3780e684faf9716295d76fe3406.png
[809c9e431b2f486397512da3a181855b.png]: https://img-blog.csdnimg.cn/809c9e431b2f486397512da3a181855b.png