# Packages to be used
library(tidyverse)
library(rvest)   # used to manipulate HTML 
#> Warning: package 'rvest' was built under R version 4.0.4
library(XML)
#> Warning: package 'XML' was built under R version 4.0.4
library(xml2)
library(jsonlite)

Problem Overview

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”). To help you better understand the different file structures, I’d prefer that you create each of these files “by hand” unless you’re already very comfortable with the file formats. 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?

Read the data from HTML, XML, and JSON source files

Read book data from an HTML file

Read book data from an HTML file and store it in a dataframe

books_html <- rvest::read_html("Books.html")
df_html <- books_html %>%
  html_element("table") %>%
  html_table()

Read book data from an XML file

Read book data from an XML file and store it in a dataframe

books_xml <- XML::xmlParse("Books.xml")
root_xml <- XML::xmlRoot(books_xml)
df_xml <- xmlToDataFrame(root_xml)

Read book data from a JSON file

Read book data from an JSON file and store it in a dataframe

books_json <- jsonlite::read_json("Books.json", simplifyVector = TRUE)
df_json <- books_json$Books

Compare the data type of the 3 resulting variables holding the content of the read files

The resulting data types for HTML, XML and JSON sources are different.

class(books_html)

[1] “xml_document” “xml_node”

class(books_xml)

[1] “XMLInternalDocument” “XMLAbstractDocument”

class(books_json)

[1] “list”

Compare the Output of the 3 resulting dataframes

The resulting content of the dataframes for all three sources are different.

Dataframe output from HTML source:

The authors columns are repeated for each author and are filled with “NA” when fewer authors exist

BookTitle BookISBN13 BookISBN10 Publisher Pages Authors Authors Authors Authors Authors
The Data Warehouse Lifecycle Toolkit 2nd Edition 978-0470149775 470149779 Wiley; 2nd edition (January 10, 2008) 672 Ralph Kimball Margy Ross Warren Thornthwaite Joy Mundy Bob Becker
T-SQL Window Functions: For data analysis and beyond (Developer Reference) 2nd Edition 978-0135861448 135861446 Microsoft Press; 2nd edition (November 4, 2019) 352 Itzik Ben-Gan NA NA NA NA
Microsoft Power BI Quick Start Guide: Build dashboards and visualizations to make your data come to
life 978-1789138221 1789138221 Packt Publishing (July 30, 2018) 200 Devin Knight Brian Knight Mitchell Pearson Manuel Quintana NA

Dataframe output from XML source:

The authors names are combined in one column but they are separated by single spaces

BookTitle BookISBN13 BookISBN10 Publisher Pages Authors
The Data Warehouse Lifecycle Toolkit 2nd Edition 978-0470149775 0470149779 Wiley; 2nd edition (January 10, 2008) 672 Ralph KimballMargy RossWarren ThornthwaiteJoy MundyBob Becker
T-SQL Window Functions: For data analysis and beyond (Developer Reference) 2nd Edition 978-0135861448 0135861446 Microsoft Press; 2nd edition (November 4, 2019) 352 Itzik Ben-Gan
Microsoft Power BI Quick Start Guide: Build dashboards and visualizations to make your data come to life 978-1789138221 1789138221 Packt Publishing (July 30, 2018) 200 Devin KnightBrian KnightMitchell PearsonManuel Quintana

Dataframe output from JSON source:

The authors names are combined in one column but they are separated by commas

BookTitle BookISBN13 BookISBN10 Publisher Pages Authors
The Data Warehouse Lifecycle Toolkit 2nd Edition 978-0470149775 0470149779 Wiley; 2nd edition (January 10, 2008) 672 Ralph Kimball , Margy Ross , Warren Thornthwaite, Joy Mundy , Bob Becker
T-SQL Window Functions: For data analysis and beyond (Developer Reference) 2nd Edition 978-0135861448 0135861446 Microsoft Press; 2nd edition (November 4, 2019) 352 Itzik Ben-Gan
Microsoft Power BI Quick Start Guide: Build dashboards and visualizations to make your data come to life 978-1789138221 1789138221 Packt Publishing (July 30, 2018) 200 Devin Knight , Brian Knight , Mitchell Pearson, Manuel Quintana

Compare the data type of the 3 resulting dataframes

The resulting data types for XML and JSON are the same, but the HTML is not.

class(df_html)

[1] “tbl_df” “tbl” “data.frame”

class(df_xml)

[1] “data.frame”

class(df_json)

[1] “data.frame”