数据可视化思维导图

U785595061

2024-12-17

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类别数据

数据分布

样本相似性

类别数据，数据分布，变量关系可视化内容讲解

树图思维导图提供《数据可视化》在线思维导图免费制作，点击“编辑”按钮，可对《数据可视化》进行在线思维导图编辑，本思维导图属于思维导图模板主题，文件编号是：636a50eb9144e89a9163606e86b1f838

思维导图大纲

类别数据可视化

条形图及其变种

简单条形图

# 图形布局和设置 layout(matrix(c(1,2,3,3),2,2,byrow=TRUE)) # 页面布局 par(mai=c(0.6,0.6,0.3,0.1),cex=0.7,font.main=1) # 绘制性别的水平条形图 barplot(table2,xlab="人数",ylab="性别", horiz=TRUE, density=30,angle=0, col=c("grey50","grey80"),border="black", main="(a) 水平条形图") # 绘制态度和社区的垂直条形图 barplot(table3,xlab="态度",ylab="人数",density=20,angle=90, col=c("red","blue"),border=c(2,4),main="(b) 垂直条形图") barplot(table1,xlab="社区",ylab="人数",cex.names=1.2,cex.lab=1.2, col=c("#FEE5D9","#E78AC3","#66C2A5","#FFD92F"),main="(c) 垂直条形图")

帕累托图

par(mai=c(0.7,0.7,0.2,1),cex=0.8) tab<-sort(table(example3_1$社区),decreasing=TRUE) palette<-RColorBrewer::brewer.pal(4,"Blues") bar<-barplot(tab,xlab="社区",ylab="频数",col=palette,ylim=c(0,1.2*max(tab))) text(bar,tab,labels=tab,pos=3,col="black")

并列条形图和堆叠条形图

par(mfrow=c(2,2),mai=c(0.7,0.7,0.65,0.7),cex=0.8,cex.main=1.2,font.main=4) tab1<-table(性别,社区);tab1 b1<-barplot(tab1,beside=T,xlab="社区",ylab="人数",ylim = c(0,1.2*max(tab1)), main="垂直并列条形图",col=c("#66C2A5","#FC8D62"),legend=rownames(tab1), args.legend=list(x=14,y=22,ncol=1,cex=1,box.col="grey80",bty='n')) #使用DescTools包添加频数标签 library(DescTools) BarText(tab1,b=b1,beside=T,horiz=F,cex=0.8) tab2<-table(性别,态度);tab2 b2<-barplot(tab2,beside=T,horiz=T,xlab="人数",ylab="态度",xlim = c(0,1.4*max(tab2)), main="水平并列条形图",col=c("#66C2A5","#FC8D62"),legend=rownames(tab2), args.legend=list(x=30,y=7.2,ncol=2,cex=0.7,box.col="grey80",bty='n')) BarText(tab2,b=b2,beside=T,horiz=T,cex=0.8) tab3<-table(社区,态度);tab3 b3<-barplot(tab3,xlab="态度",ylab="人数",main="垂直堆叠条形图", col=c("#FC8D62","#E78AC3","#66C2A5","#FFD92F"),legend=rownames(tab3), args.legend=list(x=1.32,y=56,ncol=2,cex=0.7,box.col="grey80",bty='n')) BarText(tab3,b=b3,beside=F,horiz=F,cex=1,pos='mid') b4<-barplot(tab3,horiz=T,xlab="人数",ylab="态度", main="水平堆叠条形图",col=c("#FC8D62","#E78AC3","#66C2A5","#FFD92F"), legend=rownames(tab3),args.legend=list(x=47,y=3, ncol=2,cex=0.7,box.col="grey80",bty='n')) BarText(tab3,b=b4,beside=F,horiz=T,col="black",cex=0.8,pos='mid')

脊形图

par(mfrow=c(1,2),mai=c(0.7,0.7,0.4,0.4),cex=0.8,cex.main=1,font.main=1) palette<-rev(RColorBrewer::brewer.pal(4,"Blues")) spineplot(factor(性别)~factor(社区),data=example3_1, col=palette[1:2],xlab="社区",ylab="性别",main="(a) 性别与社区的脊形图") spineplot(factor(社区)~factor(态度),data=example3_1, col=palette,xlab="态度",ylab="社区",main="(b) 社区与态度的脊形图")

百分比条形图

library("ggiraphExtra") require(ggplot2) ggSpine(data=example3_1,aes(x=态度,fill=社区), palette="Blues",labelsize=3,reverse = T)

马塞克图

mosaicplot(~性别+社区+态度,data=example3_1, col=c("#E41A1C","#377EB8"), cex.axis =0.8,off=5,main="")

树状图

treemap(df,index=c("社区","性别","态度"), vSize="频数", type="index", fontsize.labels=9, position.legend="bottom", title="")

饼图及其变种

饼图

par(mai=c(0.2,0.2,0.2,0.2),cex=0.8,font.main=1) tab<-table(example3_1$社区) name<-names(tab) percent<-round(prop.table(tab)*100,2) labs<-paste(name," ",percent,"%",sep="") palette<-RColorBrewer::brewer.pal(4,"Set3") pie(tab,labels=labs,init.angle=90,col=palette)

扇形图

library(plotrix) library(RColorBrewer) palette<-RColorBrewer::brewer.pal(4,"Set3") par(mai=c(0.3,0.3,0.5,0.8),cex=0.6,font.main=1) fan.plot(tab,labels=labs,col=palette, max.span=0.9*pi, shrink=0.1,radius=1, label.radius=1.2,ticks=200)

环形图和饼环图

library(ggiraphExtra);require(ggplot2);library(gridExtra) p1<-ggDonut(example3_1,aes(donuts=社区),colour="white", xmin=2,xmax=4,title="(a) 环形图") # 绘制饼环图 p2<-ggPieDonut(data=example3_1,aes(pies=社区,donuts=态度), title="(b) 饼环图") grid.arrange(p1,p2,ncol=2) # 按2列组合图形p1和p2

数据分布可视化

直方图

par(mfrow=c(2,3),mai=c(0.4,0.5,0.4,0.1),cex=0.7,mgp=c(2,1,0),cex.main=1,font.main=1) hist(北京,labels=TRUE,col="#FFD92F",xlab="AQI",ylab="频数", ylim=c(0,100),xlim=c(0,300),main="(a) 北京：添加频数标签") hist(上海,breaks=20,col="skyblue",xlab="AQI",ylab="频数", ylim=c(0,100),xlim=c(0,300),main="(b) 上海：数据分成20组") hist(郑州,breaks=20,col="lightgreen",xlab="AQI",ylab="频数",xlim=c(0,300), main="(c) 郑州：添加地毯图") rug(郑州) hist(武汉,breaks=20,col="#FC8D62",xlab="AQI",ylab="频数",xlim=c(0,300), main="(d) 武汉：添加扰动点") rug(jitter(武汉)) hist(西安,prob=TRUE,breaks=20,col="pink",xlab="AQI",ylab="密度", ylim=c(0,0.012),xlim=c(0,300),main="(e) 西安：添加核密度曲线") lines(density(西安),col="blue3",lwd=1) hist(沈阳,prob=TRUE,breaks=20,col="orange",xlab="AQI",ylab="密度",xlim=c(0,300),xaxs='i',yaxs='i', main="(f) 沈阳：添加理论正态分布曲线") curve(dnorm(x,mean(沈阳),sd(沈阳)),col="green",add=T)

核密度图

library(reshape2);library(DescTools) df<-melt(example3_2,id.vars=c("日期"),variable.name="城市", value.name="AQI")# 将数据融合成长格式 par(mfrow=c(2,1),mai=c(0.7,0.7,0.3,0.1),cex=0.7,font.main=1) PlotMultiDens(data=df,AQI~城市,col=Pal(),xlab="AQI",ylab="Density", xlim=c(-1,350),lwd=1,main="(a) 核密度曲线") PlotMultiDens(data=df,AQI~城市,xlab="AQI",ylab="Density", xlim=c(-1,350),lwd=1,fill=SetAlpha(rainbow(6),0.2),# 设置填充颜色和透明度 main="(b) 填充颜色")

箱线图

# 6个城市AQI的箱形图 par(mai=c(0.6,0.6,0.1,0.1),cex=0.7) library(RColorBrewer) palette<-RColorBrewer::brewer.pal(6,"Set2") dev.new() boxplot(example3_2[,2:7],xlab="城市",col=palette,ylab="AQI",horizontal =F,range = 1.5) points((apply(example3_2[,2:7],2,mean)),col="blue3",lwd=2,cex=1.5,pch="+") # 画出均值点 # 6个城市AQI的小提琴图 library(vioplot) vioplot(example3_2[2:7],col=palette, names=c("北京","上海","郑州","武汉","西安","沈阳"), xlab="城市",ylab="AQI")

茎叶图

# 每个茎列出1次 library(aplpack) stem.leaf(example3_2$北京,unit=1,m=1)# 数据的单位为1，每个茎的行数为1

# 背靠背茎叶图 stem.leaf.backback(example3_2$北京[1:182],example3_2$北京[183:366],back.to.back = TRUE)

变量间关系可视化

散点图

par(mai=c(0.9,0.9,0.1,0.1),cex=0.8,cex.main=1) plot(example3_3$总股本,example3_3$每股收益,pch=19,col="green4", xlab="总股本",ylab="每股收益") abline(lm(example3_3$每股收益~example3_3$总股本),lwd=2,col="red")

p1<-ggscatterhist(example3_3,x="总股本",y="每股收益", title="边际图为直方图的散点图", size=1.5,color="forestgreen", rug=TRUE, margin.plot="histogram", margin.params=list(fill="deepskyblue",color="black"), # 设置边际图的填充颜色和线的颜色 ggtheme=theme_minimal())

p2<-ggscatterhist(example3_3,x="总股本",y="每股收益", title="边际图为核密度图的散点图", size=1.5,color="forestgreen", rug=TRUE, margin.plot="density", margin.params=list(fill="deepskyblue",color="black"), ggtheme=theme_minimal())

散点图矩阵

library(car) scatterplotMatrix(~总股本+每股收益+每股净资产+每股现金流量,example3_3, diagonal=TRUE, # 对角线绘制出核密度图 ellipse=TRUE, # 绘制椭圆 col="steelblue3", # 设置颜色 gap=0.5)

样本相似性可视化

点图

df<-reshape2::melt(example3_2,variable.name="城市",value.name="AQI") par(mai=c(0.9,0.9,0.2,0.2),mgp=c(4,2,1),cex=0.7,font=2) palette<-rev(RColorBrewer::brewer.pal(6,"Set2")) dotchart(df$AQI,groups=df$城市,gcolor=palette,lcolor="grey95",pch="o", col=palette[df$城市],pt.cex=0.3,xlab="AQI",ylab="城市")

轮廓图

library(DescTools) mat<-as.matrix(example3_4[,2:9]);rownames(mat)=as.matrix((example3_4[,1] )) # 将数据框转换成矩阵 par(mai=c(0.6,0.6,0.1,0.1),cex=0.6) PlotLinesA(t(mat),xlab="消费项目",ylab="支出金额",args.legend=NA, col=rainbow(12),pch=21,pch.col=1,pch.bg="white",pch.cex=1) legend(x="topright",legend=rownames(mat),lty=1, col=rainbow(12),box.col="grey80",inset=0.01,ncol=1,cex=0.8) # 添加图例

雷达图

library(ggiraphExtra);library(ggplot2) ggRadar(data=example3_4,rescale=FALSE,aes(group=地区),alpha=0,size=1.5)+ # 按地区分组 theme(axis.text=element_text(size=6), # 设置坐标轴字体大小 legend.position="right", # 设置图例位置 legend.text=element_text(size="6"))+ # 设置图例字体大小 theme_bw()

星图

mat<-as.matrix(example3_4[,2:9]);rownames(mat)=as.matrix((example3_4[,1] )) stars(mat,ncol=4, full=TRUE, scale=TRUE, len=0.8, draw.segments=TRUE,key.loc=c(6,0,3), mar=c(15,0.1,0.1,0.1), cex=0.8)

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