This assignment asks to prepare 3 separate files with the same data in order to practice loading the formats into R, convert them to data frames and compare the differences. The 3 formats are: HTML, JSON and XML. Each file contains data on three of my favorite books and includes the following attributes: the title, the author(s), the theme, the publication year and the number of editions. Each of the files was manually written and then loaded into Github for reference / reproducibility.
url1 <-"https://raw.githubusercontent.com/Heleinef/Data-Science-Master_Heleine/main/Books.html"
books_html <- getURL(url1)
# The HTML file loaded as class "character"
class(books_html)## [1] "character"To read the HTML file into R, I’ll need to extract books’ information from the html file using regular expressions
# Splitting the HTML content into individual book sections
book_sections <- strsplit(books_html, "</ul>")
# Creating empty lists to store extracted data
book_titles <- list()
book_titles_text <- list()
book_info <- list()
# Extract book titles and information
for (section in book_sections) {
book_title <- gsub("<h2>|</h2>", "", regmatches(section, regexec("<h2>.*?</h2>", section))[[1]])
book_title_text <- unlist(strsplit(book_title, "\n"))
book_info_section <- unlist(strsplit(section, "\n"))
book_titles <- append(book_titles, list(book_title))
book_titles_text <- append(book_titles_text, list(book_title_text))
book_info <- append(book_info, list(book_info_section))
}
# Create a data frame
books_data_html <- data.frame(
Title = unlist(sapply(book_info, function(x) gsub("<li><strong>Title:</strong> ", "", x[which(grepl("<li><strong>Title:", x))], fixed = TRUE))),
Author = unlist(sapply(book_info, function(x) gsub("<li><strong>Author:</strong> ", "", x[which(grepl("<li><strong>Author:", x))], fixed = TRUE))),
Publisher = unlist(sapply(book_info, function(x) gsub("<li><strong>Publisher:</strong> ", "", x[which(grepl("<li><strong>Publisher:", x))], fixed = TRUE))),
Publication = unlist(sapply(book_info, function(x) gsub("<li><strong>Publication:</strong> ", "", x[which(grepl("<li><strong>Publication:", x))], fixed = TRUE))),
Theme = unlist(sapply(book_info, function(x) gsub("<li><strong>Theme:</strong> ", "", x[which(grepl("<li><strong>Theme:", x))], fixed = TRUE)))
)
# Print the data frame
books_data_html## Title
## 1 Farewell to Arms</li>
## 2 War and Peace</li>
## 3 International Law: Laws, Norms, Actors: A Problem-Oriented Approach</li>
## Author
## 1 Ernest Hemingway</li>
## 2 Leo Tolstoy</li>
## 3 Jeffrey L. Dunoff and Steven R. Ratner</li>
## Publisher Publication
## 1 Charles Scribner\\'s Sons</li> 1929</li>
## 2 Various (Public Domain)</li> 1869</li>
## 3 Wolters Kluwer</li> 2020</li>
## Theme
## 1 War and Love</li>
## 2 Historical Epic</li>
## 3 International Law</li>library(rjson)
url2 <- "https://raw.githubusercontent.com/Heleinef/Data-Science-Master_Heleine/main/books.json"
books_json <- fromJSON(file = url2)
class(books_json)## [1] "list"library(tidyverse)
# Converting the list into a data frame
books_data_json_df <- data.frame(do.call("rbind", books_json))
# Unnesting the data and convert them back into a data frame
books_data_json_df <- unnest(books_data_json_df, cols = c(Title, Author, Publisher, Publication, Theme)) %>% data.frame()
class(books_data_json_df)## [1] "data.frame"books_data_json_df## Title
## 1 Farewell to Arms
## 2 War and Peace
## 3 International Law: Laws, Norms, Actors: A Problem-Oriented Approach
## Author Publisher Publication
## 1 Ernest Hemingway Charles Scribner's Sons 1929
## 2 Leo Tolstoy Various (Public Domain) 1869
## 3 Jeffrey L. Dunoff and Steven R. Ratner Wolters Kluwer 2020
## Theme
## 1 War and Love
## 2 Historical Epic
## 3 International Lawurl3 <- "https://raw.githubusercontent.com/Heleinef/Data-Science-Master_Heleine/main/books.xml"
books_xml<- getURL(url3)
class(books_xml)## [1] "character" ## read the xml content
books_data_xml <- readLines(url3, warn = FALSE)
# join the lines into a single string
books_data_xml <- paste(books_xml, collapse = "\n")
# parse the XML string
books_data_xml<- xmlParse(books_xml)
# convert to a data frame
books_data_xml <- xmlToDataFrame(books_xml)
# show raw results
books_data_xml## Title
## 1 Farewell to Arms
## 2 War and Peace
## 3 International Law: Laws, Norms, Actors: A Problem-Oriented Approach
## Author Publisher Publication
## 1 Ernest Hemingway Charles Scribner's Sons 1929
## 2 Leo Tolstoy Various (Public Domain) 1869
## 3 Jeffrey L. Dunoff and Steven R. Ratner Wolters Kluwer 2020
## Theme
## 1 War and Love
## 2 Historical Epic
## 3 International LawHTML FORMAT
books_data_html## Title
## 1 Farewell to Arms</li>
## 2 War and Peace</li>
## 3 International Law: Laws, Norms, Actors: A Problem-Oriented Approach</li>
## Author
## 1 Ernest Hemingway</li>
## 2 Leo Tolstoy</li>
## 3 Jeffrey L. Dunoff and Steven R. Ratner</li>
## Publisher Publication
## 1 Charles Scribner\\'s Sons</li> 1929</li>
## 2 Various (Public Domain)</li> 1869</li>
## 3 Wolters Kluwer</li> 2020</li>
## Theme
## 1 War and Love</li>
## 2 Historical Epic</li>
## 3 International Law</li>JSON FORMAT
books_data_json_df## Title
## 1 Farewell to Arms
## 2 War and Peace
## 3 International Law: Laws, Norms, Actors: A Problem-Oriented Approach
## Author Publisher Publication
## 1 Ernest Hemingway Charles Scribner's Sons 1929
## 2 Leo Tolstoy Various (Public Domain) 1869
## 3 Jeffrey L. Dunoff and Steven R. Ratner Wolters Kluwer 2020
## Theme
## 1 War and Love
## 2 Historical Epic
## 3 International LawXML FORMAT
books_data_xml## Title
## 1 Farewell to Arms
## 2 War and Peace
## 3 International Law: Laws, Norms, Actors: A Problem-Oriented Approach
## Author Publisher Publication
## 1 Ernest Hemingway Charles Scribner's Sons 1929
## 2 Leo Tolstoy Various (Public Domain) 1869
## 3 Jeffrey L. Dunoff and Steven R. Ratner Wolters Kluwer 2020
## Theme
## 1 War and Love
## 2 Historical Epic
## 3 International LawEach file format behaves differently when read into R. But, all the three formats rendered the entirety of the information that was stored in them. I had more trouble reading the html format into R despite having loaded the required libraries(data.table, rlist and rvest). Fortunately regular expressions came handy and helped me circumvent the issue I faced.