《人工智能基础及应用（Python 微课版）》程序代码 第3章 数据可视化

第3章数据可视化【例3.1】Matplotlib绘图举例importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnp#让中文正常显示matplotlib.rcParams['font.family']='KaiTi'matplotlib.rcParams['axes.unicode_minus']=False#解决负号显示成方块的问题#π×2的正确写法是2*np.pi或2*math.pix=np.arange(0,2*np.pi,0.05)y=np.sin(x)fig=plt.figure()ax=fig.add_axes([0.1,0.1,0.8,0.8])#2.坐标轴范围别贴着边界，留一点边距ax.plot(x,y)ax.set_title('正弦曲线示例')ax.set_xlabel('横轴值')ax.set_ylabel('纵轴值')#y轴范围应该是[-1,1]，而不是[1,1]ax.set_xlim(0,2*np.pi)ax.set_ylim(-1,1)plt.show()【例3.2】subplot举例importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnpfig=plt.figure(num=1,figsize=(4,4))plt.subplot(221)#画布分为2x2的区域plt.plot([1,2,3,4],[1,2,3,4])plt.subplot(222)plt.plot([1,2,3,4],[2,2,3,4])plt.subplot(223)plt.plot([1,2,3,4],[1,2,2,4])plt.subplot(224)plt.plot([1,2,3,4],[1,2,3,3])plt.show()【例3.3】add_subplot举例importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnp#让中文正常显示fig=plt.figure(num=1,figsize=(4,4))ax1=fig.add_subplot(221)#画布分为2x2的区域rect=plt.Rectangle((0.1,0.2),0.3,0.6,color='r')#创建一个矩形，参数：(x,y),width,heightax1.add_patch(rect)#将形状添加到子图上ax2=fig.add_subplot(222)circ=plt.Circle((0.5,0.3),0.2,color='r',alpha=0.3)#创建一个椭圆，参数：中心点，半径，默认圆形随窗口大小进行长宽压缩ax2.add_patch(circ)#将形状添加到子图上ax3=fig.add_subplot(223)pgon=plt.Polygon([[0.2,0.2],[0.65,0.6],[0.2,0.6]])#创建一个多边形，参数：每个顶点坐标ax3.add_patch(pgon)#将形状添加到子图上fig.canvas.draw()#子图绘制plt.show()【例3.4】折线图举例importnumpyasnpimportmatplotlibmatplotlib.use('TkAgg')#强制走Tk图形后端，保证弹出独立窗口frommatplotlibimportpyplotaspltx=np.arange(1,11)y=2*x*x+5plt.title("plotfigure")plt.xlabel("xaxis")plt.ylabel("yaxis")plt.plot(x,y)plt.show()【例3.5】散点图举例importnumpyasnpimportmatplotlib.pyplotaspltx=np.arange(1,10)#产生测试数据y=xfig=plt.figure()ax1=fig.add_subplot(111)ax1.set_title('ScatterPlot')#设置标题plt.xlabel('X')#设置X轴标签plt.ylabel('Y')#设置Y轴标签ax1.scatter(x,y,c='r',marker='o')#画散点图plt.legend('x1')#设置图标plt.show()#显示所画的图【例3.6】饼状图举例importmatplotlib.pyplotaspltimportnumpyasnplabels=['Mon','Tue','Wed','Thu','Fri','Sat','Sun']data=np.random.rand(7)*100plt.pie(data,labels=labels,autopct='%1.1f%%')plt.axis('equal')plt.legend()plt.show()【例3.7】条形图举例importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnpplt.rcParams['font.size']=10#全局字号plt.rcParams['axes.unicode_minus']=False#解决负号显示方框labels=['Apple','Banana','Orange','Pear','Watermelon']sales=[83,61,55,47,38]fig,ax=plt.subplots(figsize=(6,4))bars=ax.bar(labels,sales,color='tomato',edgecolor='k',linewidth=0.8)#数值标签置顶forbinbars:height=b.get_height()ax.text(b.get_x()+b.get_width()/2,height+1,f'{height}',ha='center',va='bottom')ax.set_ylabel('Sales/boxes')ax.set_title('Fruitsales')plt.tight_layout()plt.show()【例3.8】箱线图举例importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnp#1.造数据np.random.seed(42)data=np.concatenate([np.random.normal(100,10,90),np.random.normal(150,15,10)])#2.画图fig,ax=plt.subplots(figsize=(6,3))bp=ax.boxplot(data,vert=False,patch_artist=True,boxprops=dict(facecolor='lightblue'),showmeans=False,widths=0.3)#3.关键数值q1,q2,q3=np.percentile(data,[25,50,75])iqr=q3-q1whis_lo=q1-1.5*iqrwhis_hi=q3+1.5*iqr#4.标注（纯英文，位置用y=0.15保证在图内）style=dict(fontsize=9,va='center',ha='center')y_txt=0.15ax.text(q1,y_txt,f'Q1\n{q1:.1f}',**style)ax.text(q2,y_txt,f'Q2\n{q2:.1f}',**style)ax.text(q3,y_txt,f'Q3\n{q3:.1f}',**style)#IQR箭头ax.annotate('',xy=(q3,0.35),xytext=(q1,0.35),arrowprops=dict(arrowstyle='<->',color='red'))ax.text((q1+q3)/2,0.4,f'IQR={iqr:.1f}',color='red',**style)#须线ax.text(whis_lo,y_txt,f'Lower\n{whis_lo:.1f}',**style)ax.text(whis_hi,y_txt,f'Upper\n{whis_hi:.1f}',**style)ax.set_xlim(50,180)ax.set_yticks([])ax.set_title('BoxplotElements')plt.tight_layout()plt.show()【例3.9】面积图举例#0.统一导入importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnpplt.rcParams['font.size']=10plt.rcParams['axes.unicode_minus']=Falsex=np.linspace(0,10,200)y=2+np.sin(x)*np.exp(-x*0.2)days=np.arange(1,8)#一周7天A=np.array([20,22,18,25,30,28,32])B=np.array([15,19,16,22,24,26,29])C=np.array([10,12,14,15,18,20,23])labels=['ProductA','ProductB','ProductC']colors=['#ff7f0e','#2ca02c','#1f77b4']plt.figure(figsize=(6,4))plt.stackplot(days,A,B,C,labels=labels,colors=colors,alpha=0.8)plt.legend(loc='upperleft')plt.title('StackedAreaChart')plt.xlabel('Day')plt.ylabel('Sales')plt.tight_layout()plt.show()【例3.10】环形图举例#0.统一导入importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnpplt.rcParams['font.size']=10plt.rcParams['axes.unicode_minus']=False#内环：大类outer_labels=['Mobile','Desktop']outer_sizes=[60,40]outer_colors=['#ff9f43','#0984e3']#外环：细分inner_labels=['iOS','Android','Win','macOS']inner_sizes=[35,25,22,18]inner_colors=['#feca57','#ff7675','#74b9ff','#a29bfe']fig,ax=plt.subplots(figsize=(6,6),subplot_kw=dict(aspect='equal'))#外环（细分数）ax.pie(inner_sizes,labels=inner_labels,colors=inner_colors,autopct='%1.1f%%',startangle=90,radius=1,#外半径wedgeprops=dict(width=0.3,edgecolor='w'))#内环（大类）ax.pie(outer_sizes,labels=outer_labels,colors=outer_colors,autopct='%1.1f%%',startangle=90,radius=0.7,#内半径wedgeprops=dict(width=0.3,edgecolor='w'))#中心白圆centre_circle=plt.Circle((0,0),0.4,fc='white')fig.gca().add_artist(centre_circle)ax.set_title('Device&OSSplitDonutChart')plt.tight_layout()plt.show()【例3.11】三维图两种创建方式方法一：利用关键字frommatplotlibimportpyplotaspltfrommpl_toolkits.mplot3dimportAxes3D#定义坐标轴fig=plt.figure()ax1=plt.axes(projection='3d')#ax=fig.add_subplot(111,projection='3d')#可以绘制多个子图方法二：利用三维轴方法frommatplotlibimportpyplotaspltfrommpl_toolkits.mplot3dimportAxes3D#定义图像和三维格式坐标轴fig=plt.figure()ax2=Axes3D(fig)【例3.12】绘制三角螺旋线importmatplotlibmatplotlib.use('TkAgg')importmatplotlib.pyplotaspltimportnumpyasnpplt.rcParams['font.size']=10plt.rcParams['axes.unicode_minus']=False#1.创建图+3D子图fig=plt.figure(figsize=(6,4))ax=fig.add_subplot(111,projection='3d')#2.数据zline=np.linspace(0,15,1000)xline=np.sin(zline)yline=np.cos(zline)#3.绘图ax.plot3D(xline,yline,zline,'gray')#4.显示plt.show()【例3.13】绘制三维散点的数据importmatplotlib.pyplotaspltimportnumpyasnpax=plt.axes(projection='3d')zdata=15*np.random.random(100)xdata=np.sin(zdata)+0.1*np.random.randn(100)ydata=np.cos(zdata)+0.1*np.random.randn(100)ax.scatter3D(xdata,ydata,zdata,c=zdata,cmap='Reds')【例3.14】绘制三维等高线图frommpl_toolkitsimportmplot3dimportmatplotlib.pyplotaspltimportnumpyasnpdeff(x,y):returnnp.sin(np.sqrt(x**2+y**2))x=np.linspace(-6,6,30)y=np.linspace(-6,6,30)X,Y=np.meshgrid(x,y)Z=f(X,Y)fig=plt.figure()ax=plt.axes(projection='3d')ax.contour3D(X,Y,Z,50,cmap='binary')ax.set_xlabel('x')ax.set_ylabel('y')ax.set_zlabel('z')#俯仰角设为60度，把方位角调整为35度ax.view_init(60,35)【例3.15】直方图举例importnumpyasnpimportmatplotlibmatplotlib.use('TkAgg')#强制Tk后端，独立窗口frommatplotlibimportpyplotaspltimportseabornassnsimportwarningswarnings.filterwarnings('ignore')#可选：样式sns.set_style('darkgrid')plt.rcParams['figure.figsize']=(8,4)plt.rcParams['figure.dpi']=100plt.rcParams['axes.unicode_minus']=False#生成100个成标准正态分布的随机数x=np.random.normal(size=100)#kde=True进行核密度估计sns.distplot(x,kde=True,hist=False)#hist为FALSE，直接绘制密度图而没有直方图plt.show()【例3.16】核密度图举例importnumpyasnpimportmatplotlibmatplotlib.use('TkAgg')#强制Tk后端，独立窗口frommatplotlibimportpyplotaspltimportseabornassnsfig,ax=plt.subplots()np.random.seed(4)#可复现Gaussian=np.random.normal(0,1,1000)#标准正态数据#1.直方图（密度尺度）ax.hist(Gaussian,bins=25,histtype="stepfilled",density=True,alpha=0.6,color='skyblue')#2.KDE曲线sns.kdeplot(Gaussian,shade=True,ax=ax,color='navy')ax.set_title('StandardNormalDistribution')ax.set_xlabel('Value')ax.set_ylabel('Density')plt.tight_layout()plt.show()【例3.17】小提琴图举例importnumpyasnpimportmatplotlibmatplotlib.use('TkAgg')#强制Tk后端，独立窗口frommatplotlibimportpyplotaspltimportseabornassnsimportwarningswarnings.filterwarnings('ignore')#可选：样式sns.set_style('darkgrid')plt.rcParams['figure.figsize']=(8,4)plt.rcParams['figure.dpi']=100plt.rcParams['axes.unicode_minus']=False#加载irisiris=sns.load_dataset('iris')#画小提琴图sns.violinplot(data=iris,palette='hls')plt.title('IrisFeaturesDistribution')plt.xlabel('Features')plt.ylabel('Value')#关键：弹出窗口plt.show()【例3.18】绘制热力图importnumpyasnpimportmatplotlibmatplotlib.use('TkAgg')#强制Tk后端，独立窗口frommatplotlibimportpyplotasplti