plt.legend(loc='best',frameon=False)#去掉图例边框plt.legend(loc='best',edgecolor='blue')#设置图例边框颜色plt.legend(loc='best',facecolor='blue')#设置图例背景颜色,若无边框,参数无效 对于边框还可以采用面向对象方式: legend = plt.legend(["First","Second"]) frame=legend.get_frame() frame.set...
import matplotlib.pyplot as plt line1, = plt.plot([1,2,3], label="Line 1", linestyle='--') line2, = plt.plot([3,2,1], label="Line 2", linewidth=4) # 为第一个线条创建图例 first_legend = plt.legend(handles=[line1], loc=1) # 手动将图例添加到当前轴域 ax = plt.gca()....
plt.subplot(2,2,2) #可以隔开,也可以不隔开 plt.plot(X,S) plt.subplot(212) plt.plot([1, 2, 3, 4], [1, 4, 9, 16]) plt.show() 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 0x06 参考 1. matplotlib命令与格式:图例legend语法及设置...
In thisPython tutorial, we will discussPut legend outside plot matplotlibin python. Here we will cover different examples related to legend outside plot usingmatplotlib. And we will also cover the following topics: Put legend outside plot matplotlib Matplotlib set legend outside plot Matplotlib set...
给图做图例,只需要在plt.plot()加上label参数即可,然后执行plt.legend()即可 x=np.linspace(-2,2,50) y1=2*x+1 y2=x**2 plt.plot(x,y2,label='up') plt.plot(x,y1,color='red',linewidth=1.0,linestyle='--',label='down') plt.legend() ...
["axes.unicode_minus"] = False import matplotlib.pyplot as plt import numpy as np x = np.linspace(-2*np.pi,2*np.pi,200) y = np.sin(x) y1 = np.cos(x) plt.plot(x,y,label = r"$\sin(x)$") plt.plot(x,y1,label = r"$\cos(x)$") plt.legend() plt.title("正弦函数和...
avail.legend(['ON', 'PLANNED', 'STOP']) #criando figura para plotar dentro do TKinter canvas_avail = FigureCanvasTkAgg(fig2, master=root) canvas_avail.get_tk_widget().place(x=10, y=0) root.mainloop() Proof: (查看英文版本获取更加准确信息)...
ax = sns.scatterplot(data=plot_df, x="x", y="y", hue='VP', palette='Spectral', style="label", markers=['^', 'o'], s=100) ax.set(xlabel=None, ylabel=None) ax.set_aspect('equal', 'datalim') # sns.move_legend(ax, bbox_to_anchor=(1.01, 1.01), loc='upper left') ...
ax2.plot(months, profit, color='tomato', marker='o', label='Profit') ax2.set_ylabel('Profit (%)', color='firebrick') plt.title('Sales vs Profit Trend') fig.legend(loc='upper right', bbox_to_anchor=(0.9, 0.85)) plt.show() ...
ax.legend() 三、高级可视化技巧精讲 3.1 三维数据渲染优化 对于三维数据可视化,Matplotlib的mplot3d工具包提供曲面图、散点云等呈现方式。关键点在于视角(Elevation/Azimuth)调整和颜色映射: frommpl_toolkits.mplot3dimportAxes3D X=np.arange(-5,5,0.25)Y=np.arange(-5,5,0.25)X,Y=np.meshgrid(X,Y)Z=np...