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...
Matplotlib 函数 boxplot() 为 y_data 的每一列或 y_data 序列中的每个向量绘制一个箱线图,因此 x_data 中的每个值对应 y_data 中的一列/一个向量。 箱线图示例。 def boxplot(x_data, y_data, base_color="#539caf", median_color="#297083", x_label="", y_label="", title=""): _, ...
所以考虑将legend_numpoints参数换作legend_scatterpoints,用于show()函数,并设置legend_scatterpoints=1。 代码改为: a=range(10) b=range(10) plot1 = list_plot(zip(a,b),plotjoined=False,color=(0,.5,1),marker='o',ticks=[range(10),range(10)],legend_label='Original Data Points',legend_colo...
plt.plot(rad,rad**2)## 添加y=x^2曲线 plt.plot(rad,rad**4)## 添加y=x^4曲线 plt.legend(['y=x^2','y=x^4']) ##第二幅子图 ax2 = p1.add_subplot(2,1,2)## 创开始绘制第2幅 plt.title('sin/cos') ## 添加标题 plt.xlabel('rad')## 添加x轴的名称 plt.ylabel('value')#...
The following steps are used to plot legend outside in matplotlib are outlined below: Defining Libraries:Import the important libraries which are required (For data creation and manipulation: Numpy and Pandas, For data visualization: pyplot from matplotlib). ...
注:“nolegend”条目会抛出很多警告,有没有办法禁用它们? 发布于 1 月前 ✅ 最佳回答: 要向函数提供额外的参数,不能使用拆分字符串。在问题示例中,拆分字符串将显示为: # data.plot(0, 1, ax=ax1, label=myLabel, *sets[i][2].split()) ...
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') ...
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 importmatplotlib.pyplotasplt x=[1,2,3,4,5]y=[2,1,4,5,6]z1=[i+jfor(i,j)inzip(x,y)]z2=[3*i-jfor(i,j...
Again, Matplotlib has a built-in way of quickly creating such a legend. It is done via the (you guessed it) plt.legend() method. Though there are several valid ways of using this, I find it easiest to specify the label of each line using the label keyword of the plot function (...
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()....