plt.legend()method is used to add a legend to the plot and we pass thebbox_to_anchorattribute and set itsxandycoordinate values. ” Legend outside the plot “ Also, check:Matplotlib change background color Matplotlib set legend center-left outside plot Here we are going to learn how to ...
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()....
1、导入模块:import matplotlib.pyplot as plt2、定义图像窗口:plt.figure()3、画图:plt.plot(x, y)4、定义坐标轴范围:x轴:plt.xlim()/y轴:plt.ylim() lim其实就是limit的缩写5、定义坐标轴名称:x轴:plt.xlabel()/plt.ylabel()6、定义坐标轴刻度及名称:plt.xticks()/plt.yticks()7、设置图像边框颜色...
x = np.linspace(0, 2, 100)fig, ax = plt.subplots() # Create a figure and an axes.l1 = ax.plot(x, x, label="linear")l2 = ax.plot(x, x ** 2, label="quadratic")l3 = ax.plot(x, x ** 3, label="cubic")ax.set_title("Simple Plot")ax.legend()plt.show()我们可以调整...
语法参数如下: matplotlib.pyplot.legend(*args, **kwargs) 常用的几个参数: 1.1 设置图列位置 plt.legend(loc='upper center') 0: ‘best' 1: ‘upper right' 2: ‘upper left' 3: ‘lower left' 4: ‘lower right' 5: ‘right' 6: ‘center left' ...
plt.legend(loc='best',facecolor='blue') #设置图例背景颜色,若无边框,参数无效 1. 2. 3. 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_facecolor('blue') 1. 2.
plot1.axes_labels_size(1.2) plot1.legend(True) plot1.show(frame=True,legend_loc='lower right',legend_markerscale=0.6,legend_font_size=10) 本来自己的原意是在legend中只出现1个圆点,1个点代表在这个二维空间中出现的10个点的意思是”Original Data Points“ ,但结果是出现了3个点,影响可读性。
l1 = ax.plot(x, x, label="linear") l2 = ax.plot(x, x ** 2, label="quadratic") l3 = ax.plot(x, x ** 3, label="cubic") ax.set_title("Simple Plot") ax.legend() plt.show() 我们可以调整他的参数,例如: 图例的位置、字体属性、大小,颜色,样式、图例中的列数,等等 可以在创建...
x=np.linspace(0,2,100)fig,ax=plt.subplots()# Create a figure and an axes.l1=ax.plot(x,x,label="linear")l2=ax.plot(x,x**2,label="quadratic")l3=ax.plot(x,x**3,label="cubic")ax.set_title("Simple Plot")ax.legend()plt.show() ...
plt.plot(x, y, label='sin(x)', color='blue') plt.xlabel('x') plt.ylabel('y') plt.title('Sine Function') plt.legend() plt.show() 上述代码通过Numpy生成等间隔的x值及对应的正弦值,再用Matplotlib绘制平滑曲线,直观呈现函数变化趋势。