ax.set_xlabel('X Label') ax.set_ylabel('Y Label') ax.set_title('Multiple Line Plots') 最后,显示图形: 代码语言:txt 复制 plt.show() 这样,就可以在Matplotlib上以编程方式绘制多个线条图。关于Matplotlib的更多详细用法和示例,您可以参考腾讯云的数据可视化解决方案产品 Matplotlib 的介绍页:Matplotlib...
x=np.linspace(0,10,100)y=np.vstack([np.sin(x+i*np.pi/4)foriinrange(4)])fori,yiinenumerate(y):plt.plot(x,yi,label=f'Line{i+1}- how2matplotlib.com')plt.title('Multiple Lines with Array Operations')plt.xlabel('x')plt.ylabel('y')plt.legend()plt.show() Python Copy Output:...
在调整布局以获得子图之间的最佳间距后,使用plt.show显示生成的可视化。 importmatplotlib.pyplotaspltimportnumpyasnp# Example datax=np.linspace(0,10,100)y1=np.sin(x)y2=np.cos(x)y3=np.tan(x)y4=np.exp(-x)# Creating Multiple Subplots for Line Plotsfig,axes=plt.subplots(nrows=2,ncols=2,fig...
It provides an API (or simply a submodule) calledpyplotthat contains different types of plots, figures, and related functions to visualize data. A line chart is a type of chart/graph that shows the relationship between two quantities on an X-Y plane. MY LATEST VIDEOS This video cannot be ...
plot.suptitle('Multiple Plots') plot.subplot(221) plot.bar(labels, values) plot.subplot(222) plot.scatter(labels, values) plot.subplot(223) plot.plot(labels, values) plot.subplot(224) plot.pie(values, labels=labels) plot.show() 本文地址:https://www.cnblogs.com/laishenghao/p/9573465.html...
4.密度和等高线图(Density and Contour Plots) 显示三维数据:在二维图表中展示三维数据,比如等高线图或热图。 函数:使用plt.contour绘制等高线图,使用plt.contourf绘制填充等高线图,使用plt.imshow绘制图片。 准备数据:使用np.meshgrid将一维数组转换为二维网格。
# Let’s add multiple plots using subplots() function# Give the required number of plots as an argument in subplots(), below function creates 2 subplotsfig, axs = plt.subplots(2)#create datax=np.linspace(0,100,10)# assign the data to the plot using axsaxs.plot(x, np.sin(x**2))...
gridspec_kw:It is used to create the grid on which multiple plots are located. subplot() vs subplots() While using thesubplots()function you can use just one line of code to produce a figure with multiple plots. On the other hand, thesubplot()function only constructs a single subplot ax...
I’ll be starting with the simplest kind of figure: a line plot, with points plotted on an X-Y Cartesian plane. What Kind of Data are we talking about? Obviously, different kinds of data require different kinds of plots. The X-Y plane is excellent for plotting relations between two ...
count() # create line plots for each zone category fig, ax = plt.subplots() l0, = ax.plot(df2A, lw=2, color='k', label='Industrial') l1, = ax.plot(df2B, lw=2, color='r', label='Commercial') l2, = ax.plot(df2C, lw=2, color='g', label='Historic Area') # ...