4.Matplotlib绘图--散点图

￡神魔★判官ぃ 2022-05-13 16:59 341阅读 0赞

**散点图：**是指在[回归分析][Link 1]中，数据点在直角坐标系平面上的[分布图][Link 2]，散点图表示因变量随[自变量][Link 3]而[变化][Link 4]的**大致趋势**，据此可以选择合适的函数[对数][Link 5]据点进行**[拟合][Link 6]**。

# 1.画点：scatter #

import matplotlib.pyplot as plt
    import numpy as np
    #画点
    plt.scatter(np.arange(5),np.arange(5))
    plt.show()

![70][]

# 2.散点图 #

x=np.random.normal(0,1,500)
    y=np.random.normal(0,1,500)
    plt.scatter(x,y,s=50,c='r',alpha=0.5)
    plt.xlim((-2,2))
    plt.ylim((-2,2))
    #去掉X/Y轴默认坐标
    plt.xticks(())
    plt.yticks(())
    plt.show()

![70 1][]

# 3.改变散点形状和颜色：这个案例来自matplotlib官网 #

import matplotlib.pyplot as plt
    import numpy as np
    # Fixing random state for reproducibility
    np.random.seed(19680801)
    N = 100
    r0 = 0.6
    x = 0.9 * np.random.rand(N)
    y = 0.9 * np.random.rand(N)
    area = (20 * np.random.rand(N))**2  # 0 to 10 point radii
    c = np.sqrt(area)
    r = np.sqrt(x * x + y * y)
    area1 = np.ma.masked_where(r < r0, area)
    area2 = np.ma.masked_where(r >= r0, area)
    plt.scatter(x, y, s=area1, marker='^', c=c)
    plt.scatter(x, y, s=area2, marker='o', c=c)
    
    plt.show()

![70 2][]

# Show the boundary between the regions:
    theta = np.arange(0, np.pi / 2, 0.01)
    plt.plot(r0 * np.cos(theta), r0 * np.sin(theta))
    plt.show()

![70 3][]

[Link 1]: https://baike.baidu.com/item/%E5%9B%9E%E5%BD%92%E5%88%86%E6%9E%90/2625498
[Link 2]: https://baike.baidu.com/item/%E5%88%86%E5%B8%83%E5%9B%BE/10396618
[Link 3]: https://baike.baidu.com/item/%E8%87%AA%E5%8F%98%E9%87%8F/6895256
[Link 4]: https://baike.baidu.com/item/%E5%8F%98%E5%8C%96/33159
[Link 5]: https://baike.baidu.com/item/%E5%AF%B9%E6%95%B0
[Link 6]: https://baike.baidu.com/item/%E6%8B%9F%E5%90%88/7505059
[70]: /images/20220504/ad400e4a9bc54ebda6a171609049268b.png
[70 1]: /images/20220504/56572996ca6e41e0833f2cbe83292405.png
[70 2]: /images/20220504/521bfa24267445ad85ff7cbe7ff3fab2.png
[70 3]: /images/20220504/f89d1f04574d4e768be6b9be6467f91a.png