# Chapter 2 Lab: Introduction to R # Basic Commands x <- c(1,3,2,5) x x = c(1,6,2) x y = c(1,4,3) length(x) length(y) x+y ls() rm(x,y) ls() rm(list=ls()) ?matrix x=matrix(data=c(1,2,3,4), nrow=2, ncol=2) x x=matrix(c(1,2,3,4),2,2) matrix(c(1,2,3,4),2,2,byrow=TRUE) sqrt(x) x^2 x=rnorm(50) y=x+rnorm(50,mean=50,sd=.1) cor(x,y) set.seed(1303) rnorm(50) set.seed(3) y=rnorm(100) mean(y) var(y) sqrt(var(y)) sd(y) # Graphics x=rnorm(100) y=rnorm(100) plot(x,y) plot(x,y,xlab="this is the x-axis",ylab="this is the y-axis",main="Plot of X vs Y") pdf("Figure.pdf") plot(x,y,col="green") dev.off() x=seq(1,10) x x=1:10 x x=seq(-pi,pi,length=50) y=x f=outer(x,y,function(x,y)cos(y)/(1+x^2)) contour(x,y,f) contour(x,y,f,nlevels=45,add=T) fa=(f-t(f))/2 contour(x,y,fa,nlevels=15) image(x,y,fa) persp(x,y,fa) persp(x,y,fa,theta=30) persp(x,y,fa,theta=30,phi=20) persp(x,y,fa,theta=30,phi=70) persp(x,y,fa,theta=30,phi=40) # Indexing Data A=matrix(1:16,4,4) A A[2,3] A[c(1,3),c(2,4)] A[1:3,2:4] A[1:2,] A[,1:2] A[1,] A[-c(1,3),] A[-c(1,3),-c(1,3,4)] dim(A) # Loading Data Auto=read.table("Auto.data") fix(Auto) Auto=read.table("Auto.data",header=T,na.strings="?") fix(Auto) Auto=read.csv("Auto.csv",header=T,na.strings="?") fix(Auto) dim(Auto) Auto[1:4,] Auto=na.omit(Auto) dim(Auto) names(Auto) # Additional Graphical and Numerical Summaries plot(cylinders, mpg) plot(Auto\$cylinders, Auto\$mpg) attach(Auto) plot(cylinders, mpg) cylinders=as.factor(cylinders) plot(cylinders, mpg) plot(cylinders, mpg, col="red") plot(cylinders, mpg, col="red", varwidth=T) plot(cylinders, mpg, col="red", varwidth=T,horizontal=T) plot(cylinders, mpg, col="red", varwidth=T, xlab="cylinders", ylab="MPG") hist(mpg) hist(mpg,col=2) hist(mpg,col=2,breaks=15) pairs(Auto) pairs(~ mpg + displacement + horsepower + weight + acceleration, Auto) plot(horsepower,mpg) identify(horsepower,mpg,name) summary(Auto) summary(mpg)