DATA607 - Week 7 Assignment

1. Pick three of your favorite books on one of your favorite subjects. At least one of the books should have more than one author. For each book, include the title, authors, and two or three other attributes that you find interesting.
   Take the information that you’ve selected about these three books, and separately create three files which store the book’s information in HTML (using an html table), XML, and JSON formats (e.g. “books.html”, “books.xml”, and “books.json”).
   Write R code, using your packages of choice, to load the information from each of the three sources into separate R data frames. Are the three data frames identical?

library(XML)
library(RCurl)

## Loading required package: bitops

library(rjson)
library(rvest)

## Warning: package 'rvest' was built under R version 3.4.4

## Loading required package: xml2

## 
## Attaching package: 'rvest'

## The following object is masked from 'package:XML':
## 
##     xml

library(rlist)

## Warning: package 'rlist' was built under R version 3.4.4

library(plyr)
library(jsonlite)

## Warning: package 'jsonlite' was built under R version 3.4.4

## 
## Attaching package: 'jsonlite'

## The following objects are masked from 'package:rjson':
## 
##     fromJSON, toJSON

library(knitr)
library(stringr)

html.url <- "https://raw.githubusercontent.com/niteen11/MSDS/master/DATA607/Week7/dataset/books.html"
html.file <- getURLContent(url = html.url)
books.html <-  html.file %>%
                readHTMLTable()
books.html.df <- as.data.frame(books.html)
colnames(books.html.df) <- str_replace(colnames(books.html.df),"NULL\\.", "")
colnames(books.html.df) <- str_replace(colnames(books.html.df),"\\.", " ")
kable(books.html.df)

Title	Authors	Type	Length	AmazonRating
How to Win Friends & Influence People	Dale Carnegi	Paperpack	288	4.5
Change or Die: The Three Keys to Change at Work and in Life	Alan Deutschman	Paperpack	256	4.5
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data	Hadley Wickham; Garrett Grolemund	Paperpack	522	4.5
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking	Foster Provost; Karen Dillon; Tom Fawcett	Paperpack	414	4.5
The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google	Scott Galloway	Kindle	320	4.5

dim(books.html.df)

## [1] 5 5

xml.url <- "https://raw.githubusercontent.com/niteen11/MSDS/master/DATA607/Week7/dataset/books.xml"
xml.file <- getURLContent(xml.url)
xml.df <- xml.file %>%
  xmlParse() %>%
  xmlToDataFrame()
dim(xml.df)

## [1] 5 5

kable(xml.df)

Title	Author	Type	Length	AmazonRating
How to Win Friends & Influence People	Dale Carnegi	Paperpack	288	4.5
Change or Die The Three Keys to Change at Work and in Life	Alan Deutschman	Paperpack	256	4.5
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data	Hadley Wickham; Garrett Grolemund	Paperpack	522	4.5
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking	Foster Provost; Karen Dillon; Tom Fawcett	Paperpack	414	4.5
The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google	Scott Galloway	Kindle	320	4.5

json.url <- "https://raw.githubusercontent.com/niteen11/MSDS/master/DATA607/Week7/dataset/books.json"
json.file <- getURLContent(json.url)
json.df <- as.data.frame(fromJSON(json.file[[1]]))
colnames(json.df) <- str_replace(colnames(json.df),"books\\.", "")
colnames(json.df) <- str_replace(colnames(json.df),"\\.", " ")
dim(json.df)

## [1] 5 5

kable(json.df)

Title	Authors	Type	Length	AmazonRating
How to Win Friends &Influence People	Dale Carnegi	Paperpack	288	4.5
Change or Die The Three Keys to Change at Work and in Life	Alan Deutschman	Paperpack	256	4.5
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data	Hadley Wickham, Garrett Grolemund	Paperpack	522	4.5
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking	Foster Provost, Karen Dillon, Tom Fawcett	Paperpack	414	4.5
The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google	Scott Galloway	Paperpack	320	4.5

books.html.df ==json.df

##      Title Authors  Type Length AmazonRating
## [1,] FALSE    TRUE  TRUE   TRUE         TRUE
## [2,] FALSE    TRUE  TRUE   TRUE         TRUE
## [3,]  TRUE   FALSE  TRUE   TRUE         TRUE
## [4,]  TRUE   FALSE  TRUE   TRUE         TRUE
## [5,]  TRUE    TRUE FALSE   TRUE         TRUE

json.df==xml.df

##   Title Authors  Type Length AmazonRating
## 1 FALSE    TRUE  TRUE   TRUE         TRUE
## 2  TRUE    TRUE  TRUE   TRUE         TRUE
## 3  TRUE   FALSE  TRUE   TRUE         TRUE
## 4  TRUE   FALSE  TRUE   TRUE         TRUE
## 5  TRUE    TRUE FALSE   TRUE         TRUE

All three data frames: html, xml, json are not identicial