# Reads the full data set, including numerical and categorical variables and labels
cereal_data_full <- read.csv(file="http://people.stat.sc.edu/hitchcock/cereal_new.csv",header=T)

# Creates a data set called cereal_numeric that contains 9 numeric variables measured on each cereal:
cereal.numeric <- cereal_data_full[,4:12]
# attaches the data frame so that we can refer to each column directly:
attach(cereal.numeric)

# creates a variable called rating that is a subjective "quality rating" of the cereal (presumably by a Consumer Reports expert):
rating <- cereal_data_full$rating

#creates vector of labels:
cereal_name <- cereal_data_full$name

# creates a categorical variable for the company that manufactures the cereal:
manufacturer <- cereal_data_full$manuf

# creates a categorical variable that categorizes the cereals as either 'hot' or 'cold'
cereal_type <- cereal_data_full$type