knitr::opts_chunk$set(message = FALSE, warning = FALSE)
The gutenbergr package helps you download and process public domain works from the Project Gutenberg collection. This includes both tools for downloading books (and stripping header/footer information), and a complete dataset of Project Gutenberg metadata that can be used to find words of interest. Includes:
gutenberg_download()that downloads one or more works from Project Gutenberg by ID: e.g.,
gutenberg_download(84)downloads the text of Frankenstein.
gutenberg_metadatacontains information about each work, pairing Gutenberg ID with title, author, language, etc
gutenberg_authorscontains information about each author, such as aliases and birth/death year
gutenberg_subjectscontains pairings of works with Library of Congress subjects and topics
This package contains metadata for all Project Gutenberg works as R datasets, so that you can search and filter for particular works before downloading.
gutenberg_metadata contains information about each work, pairing Gutenberg ID with title, author, language, etc:
For example, you could find the Gutenberg ID of Wuthering Heights by doing:
library(dplyr) gutenberg_metadata %>% filter(title == "Wuthering Heights")
In many analyses, you may want to filter just for English works, avoid duplicates, and include only books that have text that can be downloaded. The
gutenberg_works() function does this pre-filtering:
It also allows you to perform filtering as an argument:
gutenberg_works(author == "Austen, Jane") # or with a regular expression library(stringr) gutenberg_works(str_detect(author, "Austen"))
The meta-data currently in the package was last updated on
r format(attr(gutenberg_metadata, "date_updated"), '%d %B %Y').
gutenberg_download() downloads one or more works from Project Gutenberg based on their ID. For example, we earlier saw that "Wuthering Heights" has ID 768 (see the URL here), so
gutenberg_download(768) downloads this text.
f768 <- system.file("extdata", "768.zip", package = "gutenbergr") wuthering_heights <- gutenberg_download(768, files = f768, mirror = "http://aleph.gutenberg.org")
wuthering_heights <- gutenberg_download(768)
Notice it is returned as a tbl_df (a type of data frame) including two variables:
gutenberg_id (useful if multiple books are returned), and a character vector of the text, one row per line. Notice that the header and footer added by Project Gutenberg (visible here) have been stripped away.
Provide a vector of IDs to download multiple books. For example, to download Jane Eyre (book 1260) along with Wuthering Heights, do:
f1260 <- system.file("extdata", "1260.zip", package = "gutenbergr") books <- gutenberg_download(c(768, 1260), meta_fields = "title", files = c(f768, f1260), mirror = "http://aleph.gutenberg.org")
books <- gutenberg_download(c(768, 1260), meta_fields = "title")
Notice that the
meta_fields argument allows us to add one or more additional fields from the
gutenberg_metadata to the downloaded text, such as title or author.
books %>% count(title)
You may want to select books based on information other than their title or author, such as their genre or topic.
gutenberg_subjects contains pairings of works with Library of Congress subjects and topics. "lcc" means Library of Congress Classification, while "lcsh" means Library of Congress subject headings:
This is useful for extracting texts from a particular topic or genre, such as detective stories, or a particular character, such as Sherlock Holmes. The
gutenberg_id column can then be used to download these texts or to link with other metadata.
gutenberg_subjects %>% filter(subject == "Detective and mystery stories") gutenberg_subjects %>% filter(grepl("Holmes, Sherlock", subject))
gutenberg_authors contains information about each author, such as aliases and birth/death year:
What's next after retrieving a book's text? Well, having the book as a data frame is especially useful for working with the tidytext package for text analysis.
library(tidytext) words <- books %>% unnest_tokens(word, text) words word_counts <- words %>% anti_join(stop_words, by = "word") %>% count(title, word, sort = TRUE) word_counts
You may also find these resources useful:
gutenberg_authorto Wikipedia content with the WikipediR package or to pageview statistics with the wikipediatrend package
format_reversefunction for reversing "Last, First" names).
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