[2]How to adjust the size of matplotlib legend box? [3]Get legend as a separate picture in Matplotlib [4]creating-separate-legend-figure-with-matplotlib [5]Remove or adapt border of frame of legend using matplotlib [6]How to put the legend out of the plot [7]Custom legends in Matplotli...
labels自动通过绘图获取(Automatic detection of elements to be shown in the legend) # 第一种方法 ax.plot([1, 2, 3], label='Inline label') ax.legend() # 第二种方法 line, = ax.plot([1, 2, 3]) line.set_label('Label via method') ax.legend() 1. 2. 3. 4. 5. 6. 7. 2 le...
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.plot(x,x*x) plt.show() 具体实现效果: 5. 添加图例-legend 当线条过多时,我们设置不同颜色来区分不同线条。因此,需要对不同颜色线条做下标注,我们实用 legend() 接口来实现。 importnumpyasnp importmatplotlib.pyplotasplt # 显示中文 plt.rcParams[...
import matplotlib.pyplot as pltimport numpy as np# 生成数据x = np.linspace(0, 10, 100)y1 = np.sin(x)y2 = np.cos(x)# 绘制折线图plt.plot(x, y1, label='sin(x)')plt.plot(x, y2, label='cos(x)')# 添加标题和图例plt.title('Sin and Cos Functions')plt.legend()# 显示图形plt...
{"family":"Times New Roman","size":10})# 设置 legendplt.legend(prop={"family":"Times New Roman","size":10})### seaborn bar plot 设置 bar_label https://seaborn.pydata.org/generated/seaborn.barplot.htmlaxes=sns.barplot(data,x="x",y="y",hue="class")forcontainerinaxes.containers:...
This process creates a figure with two scatter plots and a legend placed at thecenter leftof the axes’ border-box. Add a Legend to the 3D Scatter Plot in Matplotlib Output: To create a legend for3Dscatter plot, we use theplot()method instead of thescatter()method; it’s because thele...
as plt# 创建指数函数的数据x = np.linspace(-2, 2, 100) # 生成-2到2之间的100个点y = np.exp(x) # 计算指数函数值# 绘制指数函数的曲线图plt.plot(x, y, label='y = e^x', color='b')# 添加标题和标签plt.title('chat')plt.xlabel('x')plt.ylabel('y')# 显示图例plt.legend()...
Matplotlib是Python中用于绘制图表和数据可视化的重要库。它提供了丰富的功能和灵活性,可用于生成各种类型的图表,从简单的折线图到复杂的三维图表。 1. 基本图表绘制 折线图 Matplotlib可以简单地绘制折线图,展示数据的趋势和变化。 importmatplotlib.pyplotasplt x=[1,2,3,4,5]y=[2,4,6,8,10]plt.plot(x,y...