调整宽度
air<-read.csv("airpollution.csv")
boxplot(air,las=1)
boxplot(air,boxwex=0.2,las=1)#boxwex调整宽度,其值与我们要画的变量个数有关应该小于1。
boxplot(air,width=c(1,2))#第二幅图的宽度是第一幅的2倍。
分类画图
metals<-read.csv("metals.csv")
boxplot(Cu~Source,data=metals,#y~group 按照Source分类，画图。
main="Summary of Copper (Cu) concentrations by Site")
boxplot(Cu~Source*Expt,data=metals,#按照Source*Expt分类画图
main="Summary of Copper (Cu) concentrations by Site")
根据各个变量的样本数不同，调整宽度
boxplot(Cu ~ Source, data = metals,varwidth=TRUE,#varwidth，大致与样本数的平方根成正比
main="Summary of Copper concentrations by Site")
添加凹槽
boxplot(Cu ~ Source, data = metals,
varwidth=TRUE,notch=TRUE, main="Summary of Copper concentrations by Site")#notch.frac 可以控制凹槽处相对于箱型的宽度。取值为0-1
是否包括异常值（outliers）
boxplot(metals[,-1],outline=FALSE,
main="Summary of metal concentrations by Site \n (without outliers)")
水平箱线图
boxplot(metals[,-1],
horizontal=TRUE,las=1,#注意，这里是horizontal，不是horiz
main="Summary of metal concentrations by Site")
颜色，边框等
boxplot(metals[,-1],
border = "white",col = "black",boxwex = 0.3,#border同时也控制中线的颜色，除非用medcol单独更改。
medlwd=1, whiskcol="black",staplecol="black",#medlwd中线宽度，whiskcol虚线颜色，staplecol虚线相接的两横线的颜色。
outcol="red",cex=0.3,outpch=19,#outlier的颜色，大小，样式
main="Summary of metal concentrations by Site")
grid(nx=NA,ny=NULL,col="gray",lty="dashed")
改变whisker的长度（outliers的定义）
boxplot(metals[,-1],
range=1,border = "white",col = "black",#range, 默认是1.5，取正值。越大，则outlier越少。
boxwex = 0.3,medlwd=1,whiskcol="black",
staplecol="black",outcol="red",cex=0.3,outpch=19,
main="Summary of metal concentrations by Site \n
(range=1) ")
boxplot(metals[,-1],
range=0,border = "white",col = "black",#range取0时，则恰好使得outlier没有。
boxwex = 0.3,medlwd=1,whiskcol="black",
staplecol="black",outcol="red",cex=0.3,outpch=19,
main="Summary of metal concentrations by Site \n (range=0)")
显示样本数目
b<-boxplot(metals[,-1],
xaxt="n",border = "white",col = "black",#先不建x轴
boxwex = 0.3,medlwd=1,whiskcol="black",
staplecol="black",outcol="red",cex=0.3,outpch=19,
main="Summary of metal concentrations by Site")
axis(side=1,at=1:length(b$names),labels=paste(b$names,"\n(n=",b$n,")",sep=""),mgp=c(3,2,0))#加坐标轴，设置边距。
install.packages("gplots")
library(gplots)#直接使用包，但有可能数字会和坐标轴重叠。
boxplot.n(metals[,-1],
border = "white",col = "black",boxwex = 0.3,
medlwd=1,whiskcol="black",staplecol="black",
outcol="red",cex=0.3,outpch=19,
main="Summary of metal concentrations by Site")#直接使用包，但有可能数字会和坐标轴重叠。可以把Top=True，把标签放在顶部。
把一个变量进行划分
cuts<-c(0,40,80)#划分区间
Y<-split(x=metals$Cu, f=findInterval(metals$Cu, cuts))#split,把x根据f分成各个group。findInterval(metals$Cu, cuts)则是根绝cuts的分类，给每个metals$Cu中的数字一个相应的标签，以方便group。
boxplot(Y,xaxt="n",
border = "white",col = "black",boxwex = 0.3,
medlwd=1,whiskcol="black",staplecol="black",
outcol="red",cex=0.3,outpch=19,
main="Summary of Copper concentrations",
xlab="Concentration ranges",las=1)
axis(1,at=1:length(clabels), labels=c("Below 0","0 to 40","40 to 80","Above 80"), lwd=0,lwd.ticks=1,col="gray")
函数化
boxplot.cuts<-function(y,cuts,...) {
Y<-split(metals$Cu, f=findInterval(y, cuts))
b<-boxplot(Y,xaxt="n",
border = "white",col = "black",boxwex = 0.3,
medlwd=1,whiskcol="black",staplecol="black",
outcol="red",cex=0.3,outpch=19,
main="Summary of Copper concentrations",
xlab="Concentration ranges",las=1,...)#... is used to symbolize extra arguments to be added if required.
clabels<-paste("Below",cuts[1])
for(k in 1:(length(cuts)-1)) {
clabels<-c(clabels, paste(as.character(cuts[k]),
"to", as.character(cuts[k+1])))
}
clabels<-c(clabels,
paste("Above",as.character(cuts[length(cuts)])))
axis(1,at=1:length(clabels),
labels=clabels,lwd=0,lwd.ticks=1,col="gray")
}
boxplot.cuts<-function(y,cuts) {
f=cut(y, c(min(y[!is.na(y)]),cuts,max(y[!is.na(y)])),
ordered_results=TRUE);
Y<-split(y, f=f)
b<-boxplot(Y,xaxt="n",
border = "white",col = "black",boxwex = 0.3,
medlwd=1,whiskcol="black",staplecol="black",
outcol="red",cex=0.3,outpch=19,
main="Summary of Copper concentrations",
xlab="Concentration ranges",las=1)
clabels = as.character(levels(f))
axis(1,at=1:length(clabels),
labels=clabels,lwd=0,lwd.ticks=1,col="gray")
}
