CS 698–Lab 2

1. Read in Home Depot Data

train <- read.csv("train.csv",header=T)
test <- read.csv("test.csv",header=T)
sample <- read.csv("sample_submission.csv",header=T)
attr <- read.csv("attributes.csv",header=T)
description <- read.csv("product_descriptions.csv",header=T)

Show the right down corner element of each file in R (namely, last row, last column).

train[nrow(train),ncol(train)]
test[nrow(test),ncol(test)]
sample[nrow(sample),ncol(sample)]
attr[nrow(attr),ncol(attr)]
description[nrow(description),ncol(description)]

2. Output the odd numbers of columns and even numbers of rows of train.csv

train_output <- train[seq(2,nrow(train),by=2),seq(1,ncol(train),by=2)]
head(train_output)
tail(train_output)

3. Save into R objects and load them, using dput, dget, dump, source, save, load, save.image

dput(train,file="train.RData")
dget("train.RData", keep.source = FALSE)
dump(c("train","test"),file="mydata.R")
rm(train,test)
source("mydata.R")
save(train,test,sample,attr,description,file = "mydata.RData")
load("mydata.RData")
save.image(file = "all.RData")

4. Install the readr Package, and use it to read in the data then. Any difference in terms of speed in loading the data?

install.packages("readr")
install.packages("rbenchmark")
library(readr)
library(rbenchmark)
train1 <- read_csv("train.csv")
test1 <- read_csv("test.csv")
attr1 <- read_csv("attributes.csv")
descr1 <- read_csv("product_descriptions.csv")
sample1 <- read_csv("sample_submission.csv")

benchmark(read_csv("train.csv"),read_csv("test.csv"),read_csv("attributes.csv"),read_csv("product_descriptions.csv"),read_csv("sample_submission.csv"),read.csv("train.csv",header=T),read.csv("test.csv",header=T),read.csv("sample_submission.csv",header=T),read.csv("attributes.csv",header=T),read.csv("product_descriptions.csv",header=T),columns=c("test","elapsed","relative"),order="relative", replications=1)