plt.scatter(x0,y0,s = 50,color = 'green') plt.plot([x0,x0],[y0,0],'--',color = 'black') plt.annotate('2x+1=y',xy=(x0,y0),xycoords='data',xytext = (+30,-30),textcoords = 'offset points', fontsize = 16,arrowprops=dict(arrowstyle = '->',connectionstyle = 'arc3...
importmatplotlib.pyplotaspltfrommpl_toolkits.mplot3dimportAxes3Dimportnumpyasnp fig=plt.figure()ax=fig.add_subplot(111,projection='3d')x,y,z=np.random.rand(3,10)ax.scatter(x,y,z)ax.annotate('3D Bold Annotation - How2matplotlib.com',xy=(x[0],y[0]),xytext=(x[0]+0.1,y[0]+0.1)...
importmatplotlib.pyplotaspltimportnumpyasnp# 创建数据x=np.linspace(0,10,100)y=np.sin(x)# 创建图表plt.figure(figsize=(10,6))plt.plot(x,y,label='sin(x)')# 添加注释plt.annotate('Maximum',xy=(np.pi/2,1),xytext=(np.pi/2,1.2),arrowprops=dict(facecolor='black',shrink=0.05),horizonta...
import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_subplot(111) x = np.arange(0.0, 5.0, 0.01) y = np.cos(2*np.pi*x) ax.plot(x, y, lw = 2) ''' xy=(横坐标,纵坐标) 箭头尖端 xytext=(横坐标,纵坐标) 文字的坐标,指的是最左边的坐标 arrowprops= { facecolor= '...
plt.scatter('a', 'b', c='c', s='d', data=data) plt.xlabel('entry a') plt.ylabel('entry b') plt.show() 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 运行结果如下: 用分类变量作图 Matplotlib允许我们将分类变量直接传递给许多绘图函数,我们可以看一下栗子: ...
1importmatplotlib.pyplot as plt2importnumpy as np34x = np.linspace(-3, 3, 50)5y1 = 2 * x + 16X0 =17Y0 = 2 * X0 + 189#figure 110plt.figure()11plt.plot(x, y1)12plt.scatter(X0, Y0, s = 30, color ='black')#在数据线上画点13plt.plot([X0, X0], [Y0, 0], color ...
以下是30个常用的Matplotlib函数和方法,收藏备用! 1. plot 2. scatter 3. bar 4. hist 5. pie 6. imshow 7. contour 8. contourf 9. subplot 10. subplots 11. title 12. xlabel 13. ylabel 14. xticks 15. yticks 16. legend 17. grid ...
The first function draws the scatterplot and the second one draws a line segment by passing 'solid' as a linestyle parameter. # Libraries import matplotlib.pyplot as plt import numpy as np import pandas as pd # Data df=pd.DataFrame({'x_pos': range(1,101), 'y_pos': np.random.randn...
使用seaborn 的 scatterplot 函数和 matplotlib 的 annotate 方法来实现注释功能。下面是一个示例代码: python import seaborn as sns import matplotlib.pyplot as plt import pandas as pd # 示例数据 data = pd.DataFrame({ 'x': [1, 2, 3, 4, 5], 'y': [5, 4, 3, 2, 1], 'label': ['a'...
importmatplotlib.pyplotasplt fig,ax=plt.subplots()ax.plot([0,1,2,3,4],[0,2,1,3,2])ax.annotate('Peak',xy=(3,3),xytext=(3.5,3.5),arrowprops=dict(facecolor='black',shrink=0.05))ax.set_title('How2matplotlib.com - Basic Annotation Example')plt.show() ...