# Remove objects and load libraries rm(list=ls()) # load library library(help="MASS") library("MASS") ### Data preview # Cars93 - Data from 93 Cars on Sale in the USA in 1993 data = Cars93 ?Cars93 names(data) # preview head(data) # number of rows and columns dim(data) # classes of data classes.data = lapply(data, class) ### Data subsetting sel.vars <- c("Manufacturer", "Model", "Type", "Min.Price", "Price", "Max.Price") data.new = data[,sel.vars] head(data.new) data.Manufacturer = data[which(data$Manufacturer=="Ford"), ] head(data.Manufacturer) dim(data.Manufacturer) data.nonUSA = data[which(data$Origin=="non-USA"), ] head(data.nonUSA) dim(data.nonUSA) data.200hp = data[which(data$Horsepower>200), ] head(data.200hp) dim(data.200hp) data.4WD = data[which(data$Type=="Sporty" & data$DriveTrain=="4WD"), ] head(data.4WD) dim(data.4WD) ### Data grouping count.models = aggregate(list(Model=data$Model), by=list(Manufacturer=data$Manufacturer), FUN=length) avg.price = aggregate(list(Min.Price=data$Min.Price,Max.Price=data$Max.Price,Price=data$Price), by=list(Manufacturer=data$Manufacturer), FUN=mean) count.models2 = aggregate(list(Model=data$Model), by=list(Type=data$Type,DriveTrain=data$DriveTrain), FUN=length)