R-Generating graphics(step 5)

[I]symbols and lines

> plot(A,B,type="b",lty=3,lwd=3,pch=15,cex=2)

pch #plot point
cex #symbols size,default=1
lty #lines type
lwd #lines weight,default=1

Specially,symbol 21~25,can custom border color(by col=) and fill color(by bg=)

[II]color

#Create a color match
> install.packages("RColorBrewer")
> library(RColorBrewer)
> n<-9
> mycolors<-brewer.pal(n,"Set1")
> barplot(rep(1,n),col=mycolors)

#multi-level grayscale
> n<-9
> mycolors<-rainbow(n)
> pie(rep(1,n),labels=mycolors,col=mycolors)
> mygrays<-gray(0:n/n)
> mygrays<-gray(0:n/n)
> pie(rep(1,n),labels=mygrays,col=mygrays)

[III]text

> opar<-par(no.readonly=TRUE)
> par(font.lab=3,cex.lab=1.5,font.main=4,cex.main=2)
> par(opar)

[IV]graphic size and boundary size

> opar<-par(no.readonly=TRUE)
> par(pin=c(4,3),mai=c(1,5,1,2))
> par(opar)

[V]title

> title(main="My Title",col.main="red",
+       sub="My Subtitle",col.sub="blue",
+       xlab="My X label",ylab="My Y label",
+       col.lab="green",cex.lab=0.75)

[VI]axis

> axis(4,at=z,labels=round(z,digits=2),col.axis="blue",las=2,cex.axis=0,7,tck=-0.1)

[VII]reference line

> abline(h=c(1,5,7),v=seq(1,10,2),lty=2,col="bule")

[VIII]legend

> legend("top;eft",inset=.0.5,title="Music Type",c("A","B"),lty=c(1,2),pch=c(15,17),col=c("red","bule"))

[IX]text annotation

> text(age,ID,row.names(singerdata),cex=0.6,pos=4,col="red")

math annotation

[X]graphics combination

#par()
> par(mfrow=c(2,2))

#layout()
> layout(matrix(c(1,1,2,3),2,2,byrow=TRUE),widths=c(3,1),heights=c(1,2))

[XI]ggplot2

1.specify the type of graph with a geometry function

2.grouping

> data(Salaries,package="car")
> library(ggplot2)
> ggplot(data=Salaries,aes(x=salary,fill=rank)) + geom_density(alpha=,3)

> ggplot(Salaries,aes(x=yrs,.since.phd,y=salary,color=rank,shape=sex))+geom_point()
> ggplot(Salaries,aes(x=rank,fill=sex)) + geom_bar(position="stack")+ labs(title='position="stack"')
> ggplot(Salaries,aes(x=rank,fill=sex)) + geom_bar(position="dodge")+ labs(title='position="dodge"')
> ggplot(Salaries,aes(x=rank,fill=sex)) + geom_bar(position="fill")+ labs(title='position="fill"')
> ggplot(Salaries,aes(x=rank,fill=sex)) + geom_bar()
> ggplot(Salaries,aes(x=rank)) + geom_bar(fill="red")
> ggplot(Salaries,aes(x=rank,fill="red‘’)) + geom_bar()

3.characterize

4.add a smooth curve

5.appearance

(1)axis

(2)legend

> data(Salaries,package="car")
> library(ggplot2)
> ggplot(data=Salaries,aes(x=rank,y=salary,fill=sex)) + geom_boxplot() +
            scale_x_discrete(breaks=c("AsstProf"),"AssocProf","Porf"),
            labels=c("Assistant\nProfessor","Associate\nProfessor","Full\nProfessor"))+
            scale_y_continuous(break=c(50000,100000,150000,200000),
            lables=c("$50K","$100K","$150K","$200k"))+
            labs(title="Faculty Salary by Rank and Gender",x="",y="",fill="Gender")+
            theme(legend.position=c(.1,.8))

(3)ruler

> ggplot(mtcars,aes(x=wt,y=mpg,size=disp))+geom_point(shape=21,color="black",fill="cornsilk")+
            labs(x="Weight",y="Miles Per Gallon",title="Bubble Chart",size="Engine\nDisplacement")
> data(Salaries,package="car")
> ggplot(data=Salaries,aes(x=yrs.since.phd,y=salary,color=rank))+
             scale_color_manual(values=c("orange","olivedrab","navy"))+geom_point(size=2)
> ggplot(data=Salaries,aes(x=yrs.since.phd,y=salary,color=rank))+
             scale_color_brewer(palette="Set1")+geom_point(size=2)
> library(RColorBrewer)
> display.brewer.all()

(4)theme

> data(Salaries,package="car")
> library(ggplot2)
> mytheme<-theme(plot.title=element_text(face="bold.italic",size="14",color="brown"),
                            axis.title=element_text(face="bold.italic",size=10,color="brown"),
                            axis.text=element_text(face="bold",size=9,color="darkblue"),
                            panel.background=element_rect(fill="white",color="darkblue"),
                            panel.grid.major.y=element_line(color="grey",linetype=1),
                            panel.grid.minor.y=element_line(color="grey",linetype=2),
                            panel.grid.minor.x=element_blank(),legend.position="top")

> ggplot(Salaries,aes(x=rank,y=salary,fill=sex))+geom_boxplot()+
            labs(title="Salary by Rank and Sex",x='Rank",y="Salary")+mytheme

(5)multiple map

> data(Salaries,package="car")
> library(ggplot2)
> p1<-ggplot(data=Salaries,aes(x=rank))+geom_bar()
> p2<-ggplot(data=Salaries,aes(x=sex))+geom_bar()
> p3<-ggplot(data=Salaries,aes(x=yrs.since.phd,y=salary))+geom_point()
> library(gridExtra)
> grid.arrange(p1,p2,p3,ncol=3)

5.save

> myplot<-ggplot(data=mtcars,aes(x=mpg))+geom_histogtam()
> ggsave(file="mygraph.png",plot=myplot,withd=5,height=4)

> ggplot(data=mtcars,aes(x=mpg))+geom_histogram()
> ggsave(file="mygraph.pdf")

END!