y1,label='Line 1')ax.plot(x,y2,label='Line 2')# 使用 fig.legend() 将图例放置在图形顶部fig.legend(loc='upper center',bbox_to_anchor=(0.5,1.15),ncol=2)# 调整布局plt.tight_layout()# 添加标题ax.set_title('Legend
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# Python 实现importnumpyasnpimportmatplotlib.pyplotasplt# 准备数据x=np.linspace(0,10,100)y1=np.sin(x)y2=np.cos(x)# 创建图表plt.plot(x,y1,label='sin(x)',color='blue')plt.plot(x,y2,label='cos(x)',color='orange')# 添加自定义图例plt.legend(loc='upper right',frameon=False)# 显...
# Taken from that same matplotlib doc linked earlier class HandlerEllipse(HandlerPatch): def create_artists(self, legend, orig_handle, xdescent, ydescent, width, height, fontsize, trans): center = 0.5 * width - 0.5 * xdescent, 0.5 * height - 0.5 * ydescent p = patches.Ellipse(xy=cen...
importmatplotlib.pyplotaspltfrommatplotlib.legend_handlerimportHandlerLine2DclassCustomHandler(HandlerLine2D):defcreate_artists(self,legend,orig_handle,xdescent,ydescent,width,height,fontsize,trans):line,=super().create_artists(legend,orig_handle,xdescent,ydescent,width,height,fontsize,trans)li...
Learn how to use the default legend in matplotlib Map color text to colors in chart Put directly the legend on each line Use arrows to point to the legend Advanced use case with a custom legend for a map Patterns in charts Hatchs and patternsare a great way to enhance the readability of...
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...
legend: 设置图例和其中的文本的显示 line: 设置线条(颜色、线型、宽度等)和标记 patch: 是填充2D空间的图形对象,如多边形和圆。控制线宽、颜色和抗锯齿设置等。 savefig: 可以对保存的图形进行单独设置。例如,设置渲染的文件的背景为白色。 verbose: 设置matplotlib在执行期间信息输出,如silent、helpful、debug和debug...
plt.legend(loc='best'),通过方法legend进行标签位置设置,代码中使用了best,即系统自动将标签放置在空白较多的区域,位置设置主要有以下几个:best、upper right、upper left、lower left、lower right、right、center left、center right、lower center、 upper center、center。
axhline(0, label="zorder=2.5", color="lightgrey", zorder=2.5) plt.title("Custom order of elements") l = plt.legend(loc="upper right") l.set_zorder(2.5) # legend between blue and orange line plt.show() 可以看到zorder越大,就会在最上方显示。 总结 Matplotlib在2023年6月的下载量超过...