第R語(yǔ)言實(shí)現(xiàn)各種數(shù)據(jù)可視化的超詳細(xì)教程目錄1主成分分析可視化結(jié)果1.1查看鶯尾花數(shù)據(jù)集(前五行，前四列)1.2使用鶯尾花數(shù)據(jù)集進(jìn)行主成分分析后可視化展示2圓環(huán)圖繪制3馬賽克圖繪制3.1構(gòu)造數(shù)據(jù)3.2ggplot2包的geom_rect()函數(shù)繪制馬賽克圖3.3vcd包的mosaic()函數(shù)繪制馬賽克圖3.4graphics包的mosaicplot()函數(shù)繪制馬賽克圖4棒棒糖圖繪制4.1查看內(nèi)置示例數(shù)據(jù)4.2繪制基礎(chǔ)棒棒糖圖（使用ggplot2）4.2.1更改點(diǎn)的大小，形狀，顏色和透明度4.2.2更改輔助線段的大小，顏色和類型4.2.3對(duì)點(diǎn)進(jìn)行排序，坐標(biāo)軸翻轉(zhuǎn)4.3繪制棒棒糖圖（使用ggpubr）4.3.1使用ggdotchart函數(shù)繪制棒棒糖圖4.3.2自定義一些參數(shù)5三相元圖繪制5.1構(gòu)建數(shù)據(jù)5.1.1R-ggtern包繪制三相元圖5.1.2優(yōu)化處理6華夫餅圖繪制6.1數(shù)據(jù)準(zhǔn)備6.1.1ggplot包繪制6.1.2點(diǎn)狀華夫餅圖ggplot繪制6.1.3堆積型華夫餅圖6.1.4waffle包繪制（一個(gè)好用的包，專為華夫餅圖做準(zhǔn)備的）7三維散點(diǎn)圖繪制7.1簡(jiǎn)單繪制7.2加入第四個(gè)變量，進(jìn)行顏色分組7.2.1方法一7.2.2方法二7.3用rgl包的plot3d()進(jìn)行繪制總結(jié)

1主成分分析可視化結(jié)果

1.1查看鶯尾花數(shù)據(jù)集(前五行，前四列)

iris[1:5,-5]

##Sepal.LengthSepal.WidthPetal.LengthPetal.Width

##15.13.51.40.2

##24.93.01.40.2

##34.73.21.30.2

##44.63.11.50.2

##55.03.61.40.2

1.2使用鶯尾花數(shù)據(jù)集進(jìn)行主成分分析后可視化展示

library("ggplot2")

library("ggbiplot")

##載入需要的程輯包：plyr

##載入需要的程輯包：scales

##載入需要的程輯包：grid

res.pca=prcomp(iris[,-5],scale=TRUE)

ggbiplot(res.pca,obs.scale=1,var.scale=1,ellipse=TRUE,circle=TRUE)

#添加組別顏色

ggbiplot(res.pca,obs.scale=1,var.scale=1,ellipse=TRUE,circle=TRUE,groups=iris$Species)

#更改繪制主題

ggbiplot(res.pca,obs.scale=1,var.scale=1,ellipse=TRUE,groups=iris$Species,circle=TRUE)+

theme_bw()+

theme(panel.grid=element_blank())+

scale_color_brewer(palette="Set2")+

labs(title="新主題",subtitle="好看嗎！",caption="繪于：桂林")

2圓環(huán)圖繪制

#構(gòu)造數(shù)據(jù)

df-data.frame(

group=c("Male","Female","Child"),

value=c(10,20,30))

#ggpubr包繪制圓環(huán)圖

library("ggpubr")

##載入程輯包：'ggpubr'

##Thefollowingobjectismaskedfrom'package:plyr':

##mutate

ggdonutchart(df,"value",

label="group",

fill="group",

color="white",

palette=c("#00AFBB","#E7B800","#FC4E07")

)

3馬賽克圖繪制

3.1構(gòu)造數(shù)據(jù)

library(ggplot2)

library(RColorBrewer)

library(reshape2)#提供melt()函數(shù)

library(plyr)#提供ddply()函數(shù),join()函數(shù)

df-data.frame(segment=c("A","B","C","D"),

Alpha=c(2400,1200,600,250),

Beta=c(1000,900,600,250),

Gamma=c(400,600,400,250),

Delta=c(200,300,400,250))

melt_df-melt(df,id="segment")

##segmentAlphaBetaGammaDelta

##1A24001000400200

##2B1200900600300

##3C600600400400

##4D250250250250

#計(jì)算出每行的最大，最小值，并計(jì)算每行各數(shù)的百分比。ddply()對(duì)data.frame分組計(jì)算，并利用join()函數(shù)進(jìn)行兩個(gè)表格連接。

segpct-rowSums(df[,2:ncol(df)])

for(iin1:nrow(df)){

for(jin2:ncol(df)){

df[i,j]-df[i,j]/segpct[i]*100#將數(shù)字轉(zhuǎn)換成百分比

segpct-segpct/sum(segpct)*100

df$xmax-cumsum(segpct)

df$xmin-(df$xmax-segpct)

dfm-melt(df,id=c("segment","xmin","xmax"),="percentage")

colnames(dfm)[ncol(dfm)]-"percentage"

#ddply()函數(shù)使用自定義統(tǒng)計(jì)函數(shù)，對(duì)data.frame分組計(jì)算

dfm1-ddply(dfm,.(segment),transform,ymax=cumsum(percentage))

dfm1-ddply(dfm1,.(segment),transform,ymin=ymax-percentage)

dfm1$xtext-with(dfm1,xmin+(xmax-xmin)/2)

dfm1$ytext-with(dfm1,ymin+(ymax-ymin)/2)

#join()函數(shù)，連接兩個(gè)表格data.frame

dfm2-join(melt_df,dfm1,by=c("segment","variable"),type="left",match="all")

##segmentvariablevaluexminxmaxpercentageymaxyminxtextytext

##1AAlpha2400040606002030.0

##2BAlpha12004070404005520.0

##3CAlpha6007090303008015.0

##4DAlpha25090100252509512.5

##5ABeta10000402585602072.5

##6BBeta90040703070405555.0

##7CBeta60070903060308045.0

##8DBeta250901002550259537.5

##9AGamma4000401095852090.0

##10BGamma60040702090705580.0

##11CGamma40070902080608070.0

##12DGamma250901002575509562.5

##13ADelta2000405100952097.5

##14BDelta300407010100905595.0

##15CDelta400709020100808090.0

##16DDelta2509010025100759587.5

3.2ggplot2包的geom_rect()函數(shù)繪制馬賽克圖

ggplot()+

geom_rect(aes(ymin=ymin,ymax=ymax,xmin=xmin,xmax=xmax,fill=variable),dfm2,colour="black")+

geom_text(aes(x=xtext,y=ytext,label=value),dfm2,size=4)+

geom_text(aes(x=xtext,y=103,label=paste("Seg",segment)),dfm2,size=4)+

geom_text(aes(x=102,y=seq(12.5,100,25),label=c("Alpha","Beta","Gamma","Delta")),size=4,hjust=0)+

scale_x_continuous(breaks=seq(0,100,25),limits=c(0,110))+

theme(panel.background=element_rect(fill="white",colour=NA),

panel.grid.major=element_line(colour="grey60",size=.25,linetype="dotted"),

panel.grid.minor=element_line(colour="grey60",size=.25,linetype="dotted"),

text=element_text(size=15),

legend.position="none")

3.3vcd包的mosaic()函數(shù)繪制馬賽克圖

library(vcd)

table-xtabs(value~variable+segment,melt_df)

mosaic(~segment+variable,table,shade=TRUE,legend=TRUE,color=TRUE)

包的mosaic()函數(shù)繪制馬賽克圖

library(vcd)

table-xtabs(value~variable+segment,melt_df)

mosaic(~segment+variable,table,shade=TRUE,legend=TRUE,color=TRUE)

3.4graphics包的mosaicplot()函數(shù)繪制馬賽克圖

library(graphics)

library(wesanderson)#顏色提取

mosaicplot(~segment+variable,table,color=wes_palette("GrandBudapest1"),main='')

4棒棒糖圖繪制

4.1查看內(nèi)置示例數(shù)據(jù)

library(ggplot2)

data("mtcars")

df-mtcars

#轉(zhuǎn)換為因子

df$cyl-as.factor(df$cyl)

df$name-rownames(df)

head(df)

##mpgcyldisphpdratwtqsecvsamgearcarb

##MazdaRX421.061601103.902.62016.460144

##MazdaRX4Wag21.061601103.902.87517.020144

##Datsun71022.84108933.852.32018.611141

##Hornet4Drive21.462581103.083.21519.441031

##HornetSportabout18.783601753.153.44017.020032

##Valiant18.162251052.763.46020.221031

##name

##MazdaRX4MazdaRX4

##MazdaRX4WagMazdaRX4Wag

##Datsun710Datsun710

##Hornet4DriveHornet4Drive

##HornetSportaboutHornetSportabout

##ValiantValiant

4.2繪制基礎(chǔ)棒棒糖圖（使用ggplot2）

ggplot(df,aes(name,mpg))+

#添加散點(diǎn)

geom_point(size=5)+

#添加輔助線段

geom_segment(aes(x=name,xend=name,y=0,yend=mpg))

4.2.1更改點(diǎn)的大小，形狀，顏色和透明度

ggplot(df,aes(name,mpg))+

#添加散點(diǎn)

geom_point(size=5,color="red",fill=alpha("orange",0.3),

alpha=0.7,shape=21,stroke=3)+

#添加輔助線段

geom_segment(aes(x=name,xend=name,y=0,yend=mpg))+

theme_bw()+

theme(axis.text.x=element_text(angle=45,hjust=1),

panel.grid=element_blank())

4.2.2更改輔助線段的大小，顏色和類型

ggplot(df,aes(name,mpg))+

#添加散點(diǎn)

geom_point(aes(size=cyl,color=cyl))+

#添加輔助線段

geom_segment(aes(x=name,xend=name,y=0,yend=mpg),

size=1,color="blue",linetype="dotdash")+

theme_classic()+

theme(axis.text.x=element_text(angle=45,hjust=1),

panel.grid=element_blank())+

scale_y_continuous(expand=c(0,0))

##Warning:Usingsizeforadiscretevariableisnotadvised.

4.2.3對(duì)點(diǎn)進(jìn)行排序，坐標(biāo)軸翻轉(zhuǎn)

df-df[order(df$mpg),]

#設(shè)置因子進(jìn)行排序

df$name-factor(df$name,levels=df$name)

ggplot(df,aes(name,mpg))+

#添加散點(diǎn)

geom_point(aes(color=cyl),size=8)+

#添加輔助線段

geom_segment(aes(x=name,xend=name,y=0,yend=mpg),

size=1,color="gray")+

theme_minimal()+

theme(

panel.grid.major.y=element_blank(),

panel.border=element_blank(),

axis.ticks.y=element_blank()

coord_flip()

4.3繪制棒棒糖圖（使用ggpubr）

library(ggpubr)

#查看示例數(shù)據(jù)

head(df)

##mpgcyldisphpdratwtqsecvsamgearcarb

##CadillacFleetwood10.484722052.935.25017.980034

##LincolnContinental10.484602153.005.42417.820034

##CamaroZ2813.383502453.733.84015.410034

##Duster36014.383602453.213.57015.840034

##ChryslerImperial14.784402303.235.34517.420034

##MaseratiBora15.083013353.543.57014.600158

##name

##CadillacFleetwoodCadillacFleetwood

##LincolnContinentalLincolnContinental

##CamaroZ28CamaroZ28

##Duster360Duster360

##ChryslerImperialChryslerImperial

##MaseratiBoraMaseratiBora

4.3.1使用ggdotchart函數(shù)繪制棒棒糖圖

ggdotchart(df,x="name",y="mpg",

color="cyl",#設(shè)置按照cyl填充顏色

size=6,#設(shè)置點(diǎn)的大小

palette=c("#00AFBB","#E7B800","#FC4E07"),#修改顏色畫板

sorting="ascending",#設(shè)置升序排序

add="segments",#添加輔助線段

add.params=list(color="lightgray",size=1.5),#設(shè)置輔助線段的大小和顏色

ggtheme=theme_pubr(),#設(shè)置主題

4.3.2自定義一些參數(shù)

ggdotchart(df,x="name",y="mpg",

color="cyl",#設(shè)置按照cyl填充顏色

size=8,#設(shè)置點(diǎn)的大小

palette="jco",#修改顏色畫板

sorting="descending",#設(shè)置降序排序

add="segments",#添加輔助線段

add.params=list(color="lightgray",size=1.2),#設(shè)置輔助線段的大小和顏色

rotate=TRUE,#旋轉(zhuǎn)坐標(biāo)軸方向

group="cyl",#設(shè)置按照cyl進(jìn)行分組

label="mpg",#按mpg添加label標(biāo)簽

font.label=list(color="white",

size=7,

vjust=0.5),#設(shè)置label標(biāo)簽的字體顏色和大小

ggtheme=theme_pubclean(),#設(shè)置主題

5三相元圖繪制

5.1構(gòu)建數(shù)據(jù)

test_data=data.frame(x=runif(100),

y=runif(100),

z=runif(100))

head(test_data)

##xyz

##10.795553790.11212780.90667083

##20.128166480.89807560.51703604

##30.666313570.57572050.50830765

##40.873266080.23361190.05895517

##50.010874680.76114240.37542833

##60.771264940.26820300.49992176

5.1.1R-ggtern包繪制三相元圖

library(tidyverse)

##--Attachingpackages---------------------------------------tidyverse1.3.1--

##vtibble3.1.3vdplyr1.0.7

##vtidyr1.1.3vstringr1.4.0

##vreadr2.0.1vforcats0.5.1

##vpurrr0.3.4

##--Conflicts------------------------------------------tidyverse_conflicts()--

##xdplyr::arrange()masksplyr::arrange()

##xreadr::col_factor()masksscales::col_factor()

##xpurrr::compact()masksplyr::compact()

##xdplyr::count()masksplyr::count()

##xpurrr::discard()masksscales::discard()

##xdplyr::failwith()masksplyr::failwith()

##xdplyr::filter()masksstats::filter()

##xdplyr::id()masksplyr::id()

##xdplyr::lag()masksstats::lag()

##xdplyr::mutate()masksggpubr::mutate(),plyr::mutate()

##xdplyr::rename()masksplyr::rename()

##xdplyr::summarise()masksplyr::summarise()

##xdplyr::summarize()masksplyr::summarize()

library(ggtern)

##RegisteredS3methodsoverwrittenby'ggtern':

##methodfrom

##grid.draw.ggplotggplot2

##plot.ggplotggplot2

##print.ggplotggplot2

##--

##Remembertocite,runcitation(package='ggtern')forfurtherinfo.

##--

##載入程輯包：'ggtern'

##Thefollowingobjectsaremaskedfrom'package:ggplot2':

##aes,annotate,ggplot,ggplot_build,ggplot_gtable,ggplotGrob,

##ggsave,layer_data,theme_bw,theme_classic,theme_dark,

##theme_gray,theme_light,theme_linedraw,theme_minimal,theme_void

library(hrbrthemes)

##NOTE:EitherArialNarroworRobotoCondensedfontsarerequiredtousethesethemes.

##Pleaseusehrbrthemes::import_roboto_condensed()toinstallRobotoCondensedand

##ifArialNarrowisnotonyoursystem,pleaseseehttps://bit.ly/arialnarrow

library(ggtext)

test_plot_pir-ggtern(data=test_data,aes(x,y,z))+

geom_point(size=2.5)+

theme_rgbw(base_family="")+

labs(x="",y="",

title="ExampleDensity/ContourPlot:spanGGternTest/span",

subtitle="processedmapchartswithspanggtern()/span",

caption="VisualizationbyspanDataCharm/span")+

guides(color="none",fill="none",alpha="none")+

theme(

plot.title=element_markdown(hjust=0.5,vjust=.5,color="black",

size=20,margin=margin(t=1,b=12)),

plot.subtitle=element_markdown(hjust=0,vjust=.5,size=15),

plot.caption=element_markdown(face='bold',size=12),

test_plot_pir

5.1.2優(yōu)化處理

test_plot-ggtern(data=test_data,aes(x,y,z),size=2)+

stat_density_tern(geom='polygon',n=300,

aes(fill=..level..,

alpha=..level..))+

geom_point(size=2.5)+

theme_rgbw(base_family="")+

labs(x="",y="",

title="ExampleDensity/ContourPlot:spanGGternTest/span",

subtitle="processedmapchartswithspanggtern()/span",

caption="VisualizationbyspanDataCharm/span")+

scale_fill_gradient(low="blue",high="red")+

#去除映射屬性的圖例

guides(color="none",fill="none",alpha="none")+

theme(

plot.title=element_markdown(hjust=0.5,vjust=.5,color="black",

size=20,margin=margin(t=1,b=12)),

plot.subtitle=element_markdown(hjust=0,vjust=.5,size=15),

plot.caption=element_markdown(face='bold',size=12),

test_plot

##Warning:stat_density_tern:Youhavenotspecifiedabelow-detection-limit(bdl)value(Ref.'bdl'and'bdl.val'argumentsinstat_density_tern).Presentlyyouhave2xvalue/sbelowadetectionlimitof0.010,whichacountsfor2.000%ofyourdata.DensityvaluesatfringesmayappearabnormallyhighattributedtothemathematicsoftheILRtransformation.

##Youcaneither:

##1.Ignorethiswarning,

##2.SetthebdlvalueappropriatelysothatfringevaluesareomittedfromtheILRcalculation,or

##3.Acceptthehighdensityvaluesiftheyexist,andmanuallysetthe'breaks'argument

##sothatthecountoursatlowerdensitiesarerepresentedappropriately.

6華夫餅圖繪制

6.1數(shù)據(jù)準(zhǔn)備

#相關(guān)包

library(ggplot2)

library(RColorBrewer)

library(reshape2)

#數(shù)據(jù)生成

nrows-10

categ_table-round(table(mpg$class)*((nrows*nrows)/(length(mpg$class))))

sort_table-sort(categ_table,index.return=TRUE,decreasing=FALSE)

Order-sort(as.data.frame(categ_table)$Freq,index.return=TRUE,decreasing=FALSE)

df-expand.grid(y=1:nrows,x=1:nrows)

df$category-factor(rep(names(sort_table),sort_table),levels=names(sort_table))

Color-brewer.pal(length(sort_table),"Set2")

head(df)

##yxcategory

##1112seater

##2212seater

##331minivan

##441minivan

##551minivan

##661minivan

6.1.1ggplot包繪制

ggplot(df,aes(x=y,y=x,fill=category))+

geom_tile(color="white",size=0.25)+

#geom_point(color="black",shape=1,size=5)+

coord_fixed(ratio=1)+#x,y軸尺寸固定，ratio=1表示x，y軸長(zhǎng)度相同

scale_x_continuous(trans='reverse')+#expand=c(0,0),

scale_y_continuous(trans='reverse')+#expand=c(0,0),

scale_fill_manual(name="Category",

#labels=names(sort_table),

values=Color)+

theme(#panel.border=element_rect(fill=NA,size=2),

panel.background=element_blank(),

plot.title=element_text(size=rel(1.2)),

axis.text=element_blank(),

axis.title=element_blank(),

axis.ticks=element_blank(),

legend.title=element_blank(),

legend.position="right")

##Coordinatesystemalreadypresent.Addingnewcoordinatesystem,whichwillreplacetheexistingone.

6.1.2點(diǎn)狀華夫餅圖ggplot繪制

library(ggforce)

ggplot(df,aes(x0=y,y0=x,fill=category,r=0.5))+

geom_circle(color="black",size=0.25)+

#geom_point(color="black",shape=21,size=6)+

coord_fixed(ratio=1)+

scale_x_continuous(trans='reverse')+#expand=c(0,0),

scale_y_continuous(trans='reverse')+#expand=c(0,0),

scale_fill_manual(name="Category",

#labels=names(sort_table),

values=Color)+

theme(#panel.border=element_rect(fill=NA,size=2),

panel.background=element_blank(),

plot.title=element_text(size=rel(1.2)),

legend.position="right")

##Coordinatesystemalreadypresent.Addingnewcoordinatesystem,whichwillreplacetheexistingone.

6.1.3堆積型華夫餅圖

library(dplyr)

nrows-10

ndeep-10

unit-100

df-expand.grid(y=1:nrows,x=1:nrows)

categ_table-as.data.frame(table(mpg$class)*(nrows*nrows))

colnames(categ_table)-c("names","vals")

categ_table-arrange(categ_table,desc(vals))

categ_table$vals-categ_table$vals/unit

tb4waffles-expand.grid(y=1:ndeep,x=seq_len(ceiling(sum(categ_table$vals)/ndeep)))

regionvec-as.character(rep(categ_table$names,categ_table$vals))

tb4waffles-tb4waffles[1:length(regionvec),]

tb4waffles$names-factor(regionvec,levels=categ_table$names)

Color-brewer.pal(nrow(categ_table),"Set2")

ggplot(tb4waffles,aes(x=x,y=y,fill=names))+

#geom_tile(color="white")+#

geom_point(color="black",shape=21,size=5)+#

scale_fill_manual(name="Category",

values=Color)+

xlab("1square=100")+

ylab("")+

coord_fixed(ratio=1)+

theme(#panel.border=element_rect(fill=NA,size=2),

panel.background=element_blank(),

plot.title=element_text(size=rel(1.2)),

#axis.text=element_blank(),

#axis.title=element_blank(),

#axis.ticks=element_blank(),

#legend.title=element_blank(),

legend.position="right")

##Coordinatesystemalreadypresent.Addingnewcoordinatesystem,whichwillreplacetheexistingone.

6.1.4waffle包繪制（一個(gè)好用的包，專為華夫餅圖做準(zhǔn)備的）

#waffle(parts,rows=10,keep=TRUE,xlab=NULL,title=NULL,colors=NA,size=2,flip=FALSE,reverse=FALSE,equal=TRUE,pad=0,use_glyph=FALSE,glyph_size=12,legend_pos="right")

#parts用于圖表的值的命名向量

#rows塊的行數(shù)

#keep保持因子水平（例如，在華夫餅圖中獲得一致的圖例）

library("waffle")

parts-c(One=80,Two=30,Three=20,Four=10)

chart-waffle(parts,rows=8)

print(chart)

7三維散點(diǎn)圖繪制

7.1簡(jiǎn)單繪制

library("plot3D")

#以Sepal.Length為x軸，Sepal.Width為y軸，Petal.Length為z軸。繪制箱子型box=TRUE;旋轉(zhuǎn)角度為theta=60,phi=20;透視轉(zhuǎn)換強(qiáng)度的值為3d=3;按照2D圖繪制正常刻度ticktype="detailed";散點(diǎn)圖的顏色設(shè)置bg="#F57446"

pmar-par(mar=c(5.1,4.1,4.1,6.1))#改版畫布版式大小

with(iris,scatter3D(x=Sepal.Length,y=Sepal.Width,z=Petal.Length,

pch=21,cex=1.5,col="black",bg="#F57446",

xlab="Sepal.Length",

y