Assignment - Working with HTML and Json

Author

Kingsley Kojo Kpoku

INSTALLING LIBRARIES

library(rvest)
library(jsonlite)

READING HTML / JSON FILES

html_page <- read_html("Books.html")
html_table <- html_element(html_page, "table")

## TURN THE TABLES INTO R DATAFRAME

books_from_html <- html_table(html_table)

books_from_html

# A tibble: 3 × 5
  Title                                       Authors     Year Publisher    ISBN
  <chr>                                       <chr>      <int> <chr>       <dbl>
1 The Book on Rental Property Investing       Brandon T…  2015 BiggerPo… 9.78e12
2 The Millionaire Real Estate Investor        Gary Kell…  2005 McGraw H… 9.78e12
3 The Complete Idiot’s Guide to Buying a Home Peter Ric…  2010 DK        9.78e12

## READING THE JSON FILE

books_from_json <- fromJSON("Books.json")

books_from_json

                                        title
1       The Book on Rental Property Investing
2        The Millionaire Real Estate Investor
3 The Complete Idiot’s Guide to Buying a Home
                               authors year                publisher
1                       Brandon Turner 2015 BiggerPockets Publishing
2 Gary Keller, Dave Jenks, Jay Papasan 2005              McGraw Hill
3                       Peter Richmond 2010                       DK
           isbn
1 9780990711797
2 9780071469531
3 9781101159804

## MAKING BOTH RESULTS AS DATAFRAME

books_from_html <- as.data.frame(books_from_html)
books_from_json <- as.data.frame(books_from_json)


## MAKING EVERY COLUMN AS TEXT IN BOTH DATAFRAMES

books_from_html[] <- lapply(books_from_html, as.character)
books_from_json[] <- lapply(books_from_json, as.character)

print(books_from_html)

                                        Title
1       The Book on Rental Property Investing
2        The Millionaire Real Estate Investor
3 The Complete Idiot’s Guide to Buying a Home
                               Authors Year                Publisher
1                       Brandon Turner 2015 BiggerPockets Publishing
2 Gary Keller, Dave Jenks, Jay Papasan 2005              McGraw Hill
3                       Peter Richmond 2010                       DK
           ISBN
1 9780990711797
2 9780071469531
3 9781101159804

print(books_from_json)

                                        title
1       The Book on Rental Property Investing
2        The Millionaire Real Estate Investor
3 The Complete Idiot’s Guide to Buying a Home
                               authors year                publisher
1                       Brandon Turner 2015 BiggerPockets Publishing
2 Gary Keller, Dave Jenks, Jay Papasan 2005              McGraw Hill
3                       Peter Richmond 2010                       DK
           isbn
1 9780990711797
2 9780071469531
3 9781101159804

## COMPARING THE TWO DATAFRAMES

identical(books_from_html, books_from_json)

[1] FALSE

names(books_from_html)

[1] "Title"     "Authors"   "Year"      "Publisher" "ISBN"

names(books_from_json)

[1] "title"     "authors"   "year"      "publisher" "isbn"

## after comparing i observed that the html file has the column headers in uppercase while the json file has it in lowercase and since i prefer uppercase i am going to convert the json to uppercase

MAKING BOTH DATAFRAMES UPPERCASE

names(books_from_html) <- toupper(names(books_from_html))
names(books_from_json) <- toupper(names(books_from_json))

COMPARING THE DATAFAMES - CONFIRMATION

identical(books_from_html, books_from_json)

[1] TRUE

names(books_from_html)

[1] "TITLE"     "AUTHORS"   "YEAR"      "PUBLISHER" "ISBN"

names(books_from_json)

[1] "TITLE"     "AUTHORS"   "YEAR"      "PUBLISHER" "ISBN"

CONCLUSION AND FINDINGS

In this assignment, I created HTML and JSON files containing information about three real estate books. I used R to read the information from each file into a data frame. At first, the column headings were formatted differently: the HTML headings began with capital letters, while the JSON headings were lowercase. I changed the headings to a consistent format so R could compare the data correctly. I also made the book titles uppercase in both data frames.

After these changes, I compared the two data frames to check whether they contained the same information. This assignment helped me understand how HTML tables and JSON files organize data, and how R can read and compare information stored in different formats.