【Python】matplotlib绘图 - scatter、plot函数画离散点（带有边线）

妖狐艹你老母 2022-03-01 12:14 615阅读 0赞

matplotlib更新之后发现默认的scatter函数绘制的离散点不带有边框。查阅相关文档之后发现需要对其中的参数进行设置。

官方手册：[https://matplotlib.org/api/\_as\_gen/matplotlib.pyplot.scatter.html][https_matplotlib.org_api_as_gen_matplotlib.pyplot.scatter.html]

导入相关包

import numpy as np  
    import matplotlib.pyplot as plt

**scatter函数**

绘制颜色为红色 c = 'r'

形状为圆形 marker = 'o'

x = np.arange(1,10)  
    y = x  
    fig = plt.figure()  
    ax1 = fig.add_subplot(111)  
    ax1.set_title('Scatter Plot')  
    plt.xlabel('X')  
    plt.ylabel('Y')  
    ax1.scatter(x,y,c = 'r',marker = 'o')  
    plt.legend('x1')
    plt.show()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70][]

绘制颜色为红色 c = 'r'

形状为圆形 marker = 'o'

大小为30 s=30

边框为1（越大边框越粗） linewidths=1

边框颜色为黑色 edgecolors='k'

x = np.arange(1,10)  
    y = x  
    fig = plt.figure()  
    ax1 = fig.add_subplot(111)  
    ax1.set_title('Scatter Plot')  
    plt.xlabel('X')  
    plt.ylabel('Y')  
    ax1.scatter(x,y,c = 'r', s=30, linewidths=1, marker='o',edgecolors='k' )  
    plt.legend('x1')
    plt.show()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70 1][]

**对于plot函数来说，在连线上画出点的为位置，并且描出边框。其参数与scatter其中的参数不同。**

绘制颜色为红色 c = 'r'

形状为圆形 marker = 'o'

点的大小为6 markersize = 6

x = np.arange(1,10)  
    y = x  
    fig = plt.figure()  
    ax1 = fig.add_subplot(111)  
    ax1.set_title('Scatter Plot')  
    plt.xlabel('X')  
    plt.ylabel('Y')  
    ax1.plot(x,y,c = 'r', markersize=6, marker='o')  
    plt.legend('x1')
    plt.show()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70 2][]

绘制颜色为红色 c = 'r'

形状为圆形 marker = 'o'

点的大小为6 markersize = 6

边界的颜色为黑色 markeredgecolor = 'k'

点的颜色为黄色 markerfacecolor = 'y'

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70 3][]

[https_matplotlib.org_api_as_gen_matplotlib.pyplot.scatter.html]: https://matplotlib.org/api/_as_gen/matplotlib.pyplot.scatter.html
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70]: /images/20220301/96ad7df7180c45f19165d63f184a59ce.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70 1]: /images/20220301/73e25eb616364a1cb4e012975d36de6c.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70 2]: /images/20220301/d760334ef6df4bc4af77fc66b2d2d161.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzI5NjAwMTM3_size_16_color_FFFFFF_t_70 3]: /images/20220301/ae6b4ae036684750bc83a60738e7f484.png