收藏｜28个R语言绘图的实用程序包！

作者：郑连虎

来源：阿虎定量笔记

本文约2500字，建议阅读20+分钟。

本文为大家介绍了关于R语言绘图方面28个实用程序包。

cartogram

扭曲的地图，以传达统计信息

开发

Sebastian Jeworutzki，[email protected]；Timothee Giraud；Nicolas Lambert；Roger Bivand；Edzer Pebesma

示例

# 安装并加载包install.packages("maptools")library(maptools)# 绘制非洲边界data(wrld_simpl)afr=wrld_simpl[wrld_simpl$REGION==2]plot(afr)# 安装并加载包install.packages("cartogram")library(cartogram)# 使用2005年的非洲人口数据afr_cartogram <- cartogram(afr, "POP2005", itermax=5)# 反映非洲人口特征plot(afr_cartogram)

circlize

圈圈布局、弦图

开发

Zuguang Gu，[email protected]

示例

# 安装并加载包install.packages("circlize")library(circlize)# 生成数据name=c(3,10,10,3,6,7,8,3,6,1,2,2,6,10,2,3,3,10,4,5,9,10)feature=paste("feature ", c(1,1,2,2,2,2,2,3,3,3,3,3,3,3,4,4,4,4,5,5,5,5) , sep="")dat <- data.frame(name,feature)dat <- with(dat, table(name, feature))# 绘制弦图chordDiagram(as.data.frame(dat), transparency = 0.5)

CMplot

圆形曼哈顿图

开发

[email protected]

示例

# 安装并加载包install.packages("CMplot")library("CMplot")# 绘图CMplot(gwasResults, plot.type="c", r=1.6, cir.legend=TRUE, outward=TRUE, cir.legend.col="black", cir.chr.h=.1 ,chr.den.col="orange", file="jpg", memo="", dpi=300, chr.labels=seq(1,22))

corrgram

相关系数矩阵

开发

Kevin Wright，[email protected]

示例

# 安装并加载包install.packages("iterators")install.packages("corrgram")library(iterators)library(corrgram)# 绘制相关系数矩阵图corrgram(mtcars, order=TRUE, lower.panel=panel.shade, upper.panel=panel.pie,text.panel=panel.txt, main="Correlogram of mtcar intercorrelations")

corrplot

相关系数矩阵

开发

Taiyun Wei，[email protected]；Viliam Simko，[email protected]

示例

# 安装并加载包install.packages("corrplot")library(corrplot)# 计算相关系数mycor <- cor(mtcars)# 绘制相关系数矩阵图corrplot.mixed(mycor, upper = "ellipse")

dygraphs

时间序列数据的可视化

开发

Dan Vanderkam；JJ Allaire，[email protected]；Jonathan Owen；Daniel Gromer；Petr Shevtsov；Benoit Thieurmel

示例

# 安装并加载包install.packages("dygraphs")library(dygraphs)# 时间序列data=data.frame( time=c( seq(0,20,0.5), 40), value=runif(42))str(data)dygraph(data)

ellipse

椭圆

开发

Duncan Murdoch，[email protected]；E. D. Chow

示例

# 安装并加载包install.packages("ellipse")library(ellipse)# 绘制相关系数矩阵图data(mtcars)fit <- lm(mpg ~ ., mtcars)plotcorr(summary(fit, correlation = TRUE)$correlation)

fmsb

雷达图

开发

Minato [email protected]

示例

# 安装并加载包install.packages("fmsb")library(fmsb)# 生成数据data=as.data.frame(matrix( sample( 2:20 , 10 , replace=T) , ncol=10))colnames(data)=c("math" , "english" , "biology" , "music" , "R-coding", "data-viz" , "french" , "physic", "statistic", "sport" )data=rbind(rep(20,10) , rep(0,10) , data)# 雷达图参数设置radarchart(data,axistype=1,pcol=rgb(0.2,0.5,0.5,0.9),pfcol=rgb(0.2,0.5,0.5,0.5), plwd=4, cglcol="grey", cglty=1, axislabcol="grey", caxislabels=seq(0,20,5), cglwd=0.8,vlcex=0.8)

forecast

时间序列分析

开发

Rob J Hyndman，[email protected]

示例

# 安装并加载包install.packages("forecast")library(forecast)# 使用英国每月死于肺病的人数数据fit<- auto.arima(mdeaths)# 设置置信区间forecast(fit, level=c(80, 95, 99), h=3)# 绘制时间序列趋势图plot(forecast(fit), shadecols="oldstyle")

GGally

散点图矩阵

开发

Barret Schloerke，[email protected]；Jason Crowley，[email protected]；Di Cook，[email protected]；Heike Hofmann，[email protected]；Hadley Wickham，[email protected]；Francois Briatte，[email protected]；Moritz Marbach，[email protected]；Edwin Thoen，[email protected]；Amos Elberg，[email protected]；Joseph Larmarange，[email protected]

示例

# 安装并加载包install.packages("GGally")library(GGally)# 绘制相关系数矩阵图ggpairs(mtcars, columns = c("mpg", "cyl", "disp"),upper = list(continuous = wrap("cor", size = 10)), lower =list(continuous = "smooth"))

ggplot2

丰富的数据可视化

开发

Hadley Wickham，[email protected]；Winston Chang，[email protected]

示例

# 安装并加载包install.packages("ggplot2")library(ggplot2)# 生成数据variety=rep(LETTERS[1:7], each=40)treatment=rep(c("high","low"),each=20)note=seq(1:280)+sample(1:150, 280, replace=T)data=data.frame(variety, treatment , note)# 绘制箱线图ggplot(data, aes(x=variety, y=note, fill=treatment)) +geom_boxplot()# 生成数据set.seed(345)Sector <- rep(c("S01","S02","S03","S04","S05","S06","S07"),times=7)Year <- as.numeric(rep(c("1950","1960","1970","1980","1990","2000","2010"),each=7))Value <- runif(49, 10, 100)data <- data.frame(Sector,Year,Value)# 绘制区域图ggplot(data, aes(x=Year, y=Value, fill=Sector)) + geom_area()# 安装并加载包install.packages("plotly")install.packages("gapminder")library(plotly)library(gapminder)# 绘制气泡图p <- gapminder %>% filter(year==1977) %>% ggplot( aes(gdpPercap, lifeExp, size = pop, color=continent)) + geom_point() + scale_x_log10() + theme_bw()ggplotly(p)

ggridges

叠嶂图（山峦图）

开发

Claus O. Wilke，[email protected]

示例

# 安装并加载包install.packages("ggridges")install.packages("ggplot2")library(ggridges)library(ggplot2)# 使用钻石数据head(diamonds)# 绘制叠嶂图ggplot(diamonds, aes(x = price, y = cut, fill = cut)) + geom_density_ridges() + theme_ridges() + theme(legend.position = "none")

hexbin

二维直方图

开发

Dan Carr，[email protected]；Nicholas Lewin-Koh；Martin Maechler，[email protected]；Deepayan Sarkar，[email protected]

示例

# 安装并加载包install.packages("hexbin")install.packages("RColorBrewer")library(hexbin)library(RColorBrewer)# 生成数据x <- rnorm(mean=1.5, 5000)y <- rnorm(mean=1.6, 5000)# 绘制二维散点图bin<-hexbin(x, y, xbins=40)my_colors=colorRampPalette(rev(brewer.pal(11,'Spectral')))plot(bin, main="", colramp=my_colors, legend=F)

igraph

网络图

示例

# 安装并加载包install.packages("igraph")library(igraph)# 生成数据data=matrix(sample(0:1, 400, replace=TRUE, prob=c(0.8,0.2)), nrow=20)network=graph_from_adjacency_matrix(data , mode='undirected', diag=F )# 输出网络par(mfrow=c(2,2), mar=c(1,1,1,1))plot(network, layout=layout.sphere, main="sphere")

lattice

点图、核密度图、直方图、柱状图、箱线图、散点图、带状图、平行箱线图、三维图、散点图矩阵等

开发

Deepayan Sarkar，[email protected]

示例

# 安装并加载包install.packages("lattice")library(lattice)# 查看火山数据head(volcano)# 绘制火山的三维等高线图contourplot(volcano)# 绘制火山的三维水平图levelplot(volcano)# 绘制火山的三维线框图wireframe(volcano)# 查看汽车数据head(mtcars)# 绘制箱线图bwplot(mtcars$mpg)# 绘制平行坐标图parallelplot(mtcars[1:3])# 绘制散点图矩阵splom(mtcars[c(1,3,4,5)])# 绘制带状图stripplot(mtcars$mpg~factor(mtcars$cyl))

leaflet

交互式地图

开发

Joe Cheng，[email protected]；Bhaskar Karambelkar；Yihui Xie；Hadley Wickham；Kenton Russell；Kent Johnson；Barret Schloerke；Vladimir Agafonkin；Brandon Copeland；Joerg Dietrich；Benjamin Becquet；Norkart AS；L. Voogdt；Daniel Montague；Kartena AB；Robert Kajic；Michael Bostock

示例

# 安装并加载包install.packages("leaflet")library(leaflet)# 交互式地图m=leaflet()m=addTiles(m)m

likert

李克特量表数据的可视化

开发

Jason Bryer，[email protected]；Kimberly [email protected]

示例

# 安装并加载包install.packages("likert")library(likert)# 使用PISA量表数据data(pisaitems)items28 <- pisaitems[, substr(names(pisaitems), 1, 5) == "ST24Q"]# 绘制条形图l28 <- likert(items28)summary(l28)plot(l28)

maps

地图

开发

Richard A. Becker；Allan R. Wilks；Ray Brownrigg

示例

# 安装并加载包install.packages("maps")install.packages("geosphere")library(maps)library(geosphere)# 绘制世界地图map("world")

maptools

地图

开发

Roger Bivand，[email protected]；Nicholas Lewin-Koh；Edzer Pebesma；Eric Archer；Adrian Baddeley；Nick Bearman；Hans-Jörg Bibiko；Steven Brey；Jonathan Callahan；German Carrillo；Stéphane Dray；David Forrest；Michael Friendly；Patrick Giraudoux；Duncan Golicher；Virgilio Gómez Rubio；Patrick Hausmann；Karl Ove Hufthammer；Thomas Jagger；Kent Johnson；Sebastian Luque；Don MacQueen；Andrew Niccolai；Edzer Pebesma；Oscar Perpiñán Lamigueiro；Tom Short；Greg Snow；Ben Stabler；Murray Stokely；Rolf Turner

示例

# 安装并加载包install.packages("maptools")library(maptools)# 绘制非洲边界data(wrld_simpl)afr=wrld_simpl[wrld_simpl$REGION==2]plot(afr)

performanceAnalytics

绩效指标计算与可视化

开发

Brian G. Peterson，[email protected]；Peter Carl

示例

# 安装并加载包install.packages("PerformanceAnalytics")library(PerformanceAnalytics)# 列出待计算变量mydata <-mtcars[c('mpg','cyl','disp','hp','drat')]# 绘制相关系数矩阵图chart.Correlation(mydata, histogram=TRUE, pch=19)

plotly

交互式可视化

开发

Carson Siever，[email protected]；Chris Parmer，[email protected]；Toby Hocking，[email protected]；Scott Chamberlain，[email protected]；Karthik Ram，[email protected]；Marianne Corvellec，[email protected]；Pedro Despouy，[email protected]

示例

# 安装并加载包install.packages("plotly")library(plotly)# 查看火山数据head(volcano)# 绘制火山的三维交互图p=plot_ly(z = volcano, type = "surface")p

qcc

统计质量控制

开发

Luca Scrucca，[email protected]；Greg Snow，[email protected]；Peter Bloomfield，[email protected]

示例

# 安装并加载包install.packages("qcc")library(qcc)# 均值为10的序列，加上白噪声x <- rep(10, 100) + rnorm(100)# 测试序列，均值为11new.x <- rep(11, 15) + rnorm(15)# 标记出新的点qcc(x, newdata=new.x, type="xbar.one")

qqman

曼哈顿图

开发

Stephen Turner

示例

# 安装并加载包install.packages("qqman")library(qqman)# 使用gwasResults数据绘制曼哈顿图manhattan(gwasResults, chr="CHR", bp="BP", snp="SNP", p="P" )

REmap

地图

开发

Dawei Lang，[email protected]

示例

# 安装并加载包install.packages("devtools")install_github("lchiffon/REmap")library(devtools)library(REmap)# 标注起始点origin<-c("济南","西安","成都")destination<-c("西安","成都","济南")# 制作迁徙地图dat = data.frame(origin,destination)out = remap(dat,title = "after-graduation trip ",subtitle= "zg434")plot(out)

scatterplot3d

三维散点图

开发

Uwe Ligges，[email protected]；Martin Maechler；Sarah Schnackenberg

示例

# 安装并加载包install.packages("scatterplot3d")library(scatterplot3d)# 生成数据x1=round(rnorm(100,mean=80,sd=1))x2=round(rnorm(100,mean=80,sd=5))x3=round(rnorm(100,mean=80,sd=10))x=data.frame(x1,x2,x3)# 绘制三维散点图scatterplot3d(x[1:3])

TeachingDemos

脸谱图

；

开发

Greg Snow，[email protected]

示例

# 安装并加载包install.packages("TeachingDemos")library(TeachingDemos)# 生成数据x1=round(rnorm(100,mean=80,sd=1))x2=round(rnorm(100,mean=80,sd=5))x3=round(rnorm(100,mean=80,sd=10))x=data.frame(x1,x2,x3)# 绘制脸谱图faces(x)

treemap

树图

开发

Martijn Tennekes，[email protected]

示例

# 安装并加载包install.packages("treemap")library(treemap)# 生成数据group=c("group-1","group-2","group-3")value=c(13,5,22)data=data.frame(group,value)# 绘制树图treemap(data, index="group", vSize="value", type="index")

vioplot

小提琴图

开发

Daniel Adler，[email protected]；Romain Francois，[email protected]

示例

# 安装并加载包install.packages("vioplot")library(vioplot)# 生成数据treatment=c(rep("A", 40) , rep("B", 40) , rep("C", 40) )value=c( sample(2:5, 40 , replace=T) , sample(c(1:5,12:17), 40 , replace=T), sample(1:7, 40 , replace=T) )data=data.frame(treatment,value)# 绘制小提琴图with(data , vioplot( value[treatment=="A"] , value[treatment=="B"], value[treatment=="C"], col=rgb(0.1,0.4,0.7,0.7) , names=c("A","B","C") ))