[I]symbols and lines > plot(A,B,type="b",lty=3,lwd=3,pch=15,cex=2) Parameter function pch plot point cex symbols size,default=1 lty lines type lwd lines weight,default=1
pch #plot point
cex #symbols size,default=1
lty #lines type
lwd #lines weight,default=1
R-Generating graphics(step 5) Specially,symbol 21~25,can custom border color(by col=) and fill color(by bg=)
R-Generating graphics(step 5) [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) col plot color col.axis axis scale text color col.lab axis label color col.main main title color col.sub sub title color fg foreground bg background
Color Number Hex RGB "white" 1 "#FFFFFF" rgb(1,1,1) "black" 24 "#000000" rgb(0,0,0) "bule" 26 "#0000FF" rgb(0,0,255) "brown" 32 "#A52A2A" rgb(165,42,42) "orange" 498 "#FF6100" rgb(255,215,0) "pink" 536 "#FFC0CB" rgb(255,192,203) "purpel" 547 "#800080" rgb(128,0,128 "red" 552 "#FF0000" rgb(255,0,0) "yellow" 652 "#FFFF00" rgb(255,255,0)
[III]text > opar<-par(no.readonly=TRUE)
> par(font.lab=3,cex.lab=1.5,font.main=4,cex.main=2)
> par(opar) text size cex.axis axis scale size cex.lab axis label size cex.main main title size cex.sub sub title size
font 1=Normal,2=Bold,3=Italic,4=Bold Italic,5=Symbol Font font.axis axis scale font font.lab axis label font font.main main title font font.sub sub title font pa font value(1pound=1/72inch),font vale=ps*cex family drawing text,value=serif/sans/mono
[IV]graphic size and boundary size > opar<-par(no.readonly=TRUE)
> par(pin=c(4,3),mai=c(1,5,1,2))
> par(opar) pin graphic size:width and height(inch) mai boundary size:up down left right(inch) mar boundary size:up down left right(British cent),default=c(5,4,4,2)+0.1
[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) side the relative position of the axis in the graph,1=down,2=left,3=up,4=right at scale position labels scale line text label pos intersecting another axis position value lines and scale lines color las 0=label is parallel to the coordinate axis,2=label is perpendicular to the axis tck 0=disable scale,1=plot grid lines,default=-0.01
[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")) location legend positon,bottom,bottomleft,left,topleft,top,topright,right,bottomright,center title legend title string legend legend label string vector
[IX]text annotation > text(age,ID,row.names(singerdata),cex=0.6,pos=4,col="red") text position relative position of text,1=down,2=left,3=up,4=right,offset can be set text side,1=down,2=left,3=up,4=right,adj=0:align left bottom,adj=1:align right bottom
math annotation R-Generating graphics(step 5) [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 Function Add Option geom_bar() bar chart color,fill,alpha geom_boxplot() box plot color,fill,alpha,notch,width geom_density() density plot color,fill,alpha,linetype geom_histogram() histogram color,fill,alpha,linetype,binwidth geom_hline() horizontal line geom_jitter() jitter point color,size,alpha,shape geom_line() line plot colorvalpha,linetype,size geom_point() scatter plot color,alpha,shape,size geom_rug() carpet plot color,side geom_smooth() curve fitting method,formula,color,fill,linetype,size geom_text() text annotation reference to "help" geom_violin() violin picture geom_vline() perpendicular color,alpha,linetype,size
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 Grammar Result facet_wrap(~var,ncol=n) arrange each var horizontally into an independent map of n columns facet_wrap(~var,nrow=n) arrange each var horizontally into an independent map of n rows facet_grid(rowvar~colvar) independent plot of rowvar and colvar facet_grid(rowvar~.) independent plot of each rowvar level,configured as a single column facet_grid(.~colvar) independent plot of each column level,configured as a single row
4.add a smooth curve Description method= default=smooth;lm,smooth,rlm,gam formula= y~x(default),y~log(x),y~poly(x,n),y~ns(x,n) se draw a confidence interval,default=TRUE level confidence interval level used,default=95% fullrange default=FALSE:just data;TRUE:the fit should cover the full picture
5.appearance (1)axis
Functions scale_x_continuous()&scale_y_continuous break,label,limits,=specified scale_x_discrete()&scale_y_discrete() break,label,limits,=level coord_flip() reverse the x and the y axes
(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!
