Get a table of Gutenberg work metadata that has been filtered by some common (settable) defaults, along with the option to add additional filters. This function is for convenience when working with common conditions when pulling a set of books to analyze. For more detailed filtering of the entire Project Gutenberg metadata, use the gutenberg_metadata and related datasets.

gutenberg_works(
  ...,
  languages = "en",
  only_text = TRUE,
  rights = c("Public domain in the USA.", "None"),
  distinct = TRUE,
  all_languages = FALSE,
  only_languages = TRUE
)

Arguments

...

Additional filters, given as expressions using the variables in the gutenberg_metadata dataset (e.g. author == "Austen, Jane")

languages

Vector of languages to include

only_text

Whether the works must have Gutenberg text attached. Works without text (e.g. audiobooks) cannot be downloaded with gutenberg_download

rights

Values to allow in the rights field. By default allows public domain in the US or "None", while excluding works under copyright. NULL allows any value of Rights

distinct

Whether to return only one distinct combination of each title and gutenberg_author_id. If multiple occur (that fulfill the other conditions), it uses the one with the lowest ID

all_languages

Whether, if multiple languages are given, all of them need to be present in a work. For example, if c("en", "fr") are given, whether only en/fr as opposed to English or French works should be returned

only_languages

Whether to exclude works that have other languages besides the ones provided. For example, whether to include en/fr when English works are requested

Value

A tbl_df (see the tibble or dplyr packages) with one row for each work, in the same format as gutenberg_metadata.

Details

By default, returns

  • English-language works

  • That are in text format in Gutenberg (as opposed to audio)

  • Whose text is not under copyright

  • At most one distinct field for each title/author pair

Examples

library(dplyr) gutenberg_works()
#> # A tibble: 40,737 x 8 #> gutenberg_id title author gutenberg_autho… language gutenberg_books… rights #> <int> <chr> <chr> <int> <chr> <chr> <chr> #> 1 0 NA NA NA en NA Publi… #> 2 1 "The … Jeffer… 1638 en United States L… Publi… #> 3 2 "The … United… 1 en American Revolu… Publi… #> 4 3 "John… Kenned… 1666 en NA Publi… #> 5 4 "Linc… Lincol… 3 en US Civil War Publi… #> 6 5 "The … United… 1 en American Revolu… Publi… #> 7 6 "Give… Henry,… 4 en American Revolu… Publi… #> 8 7 "The … NA NA en NA Publi… #> 9 8 "Abra… Lincol… 3 en US Civil War Publi… #> 10 9 "Abra… Lincol… 3 en US Civil War Publi… #> # … with 40,727 more rows, and 1 more variable: has_text <lgl>
# filter conditions gutenberg_works(author == "Shakespeare, William")
#> # A tibble: 79 x 8 #> gutenberg_id title author gutenberg_autho… language gutenberg_books… rights #> <int> <chr> <chr> <int> <chr> <chr> <chr> #> 1 1041 Shakes… Shake… 65 en NA Publi… #> 2 1045 Venus … Shake… 65 en NA Publi… #> 3 1500 King H… Shake… 65 en NA Publi… #> 4 1501 Histor… Shake… 65 en NA Publi… #> 5 1502 The Hi… Shake… 65 en NA Publi… #> 6 1503 The Tr… Shake… 65 en NA Publi… #> 7 1504 The Co… Shake… 65 en NA Publi… #> 8 1505 The Ra… Shake… 65 en NA Publi… #> 9 1507 The Tr… Shake… 65 en NA Publi… #> 10 1508 The Ta… Shake… 65 en NA Publi… #> # … with 69 more rows, and 1 more variable: has_text <lgl>
# language specifications gutenberg_works(languages = "es") %>% count(language, sort = TRUE)
#> # A tibble: 1 x 2 #> language n #> <chr> <int> #> 1 es 449
gutenberg_works(languages = c("en", "es")) %>% count(language, sort = TRUE)
#> # A tibble: 3 x 2 #> language n #> <chr> <int> #> 1 en 40736 #> 2 es 447 #> 3 en/es 13
gutenberg_works(languages = c("en", "es"), all_languages = TRUE) %>% count(language, sort = TRUE)
#> # A tibble: 1 x 2 #> language n #> <chr> <int> #> 1 en/es 13
gutenberg_works(languages = c("en", "es"), only_languages = FALSE) %>% count(language, sort = TRUE)
#> # A tibble: 30 x 2 #> language n #> <chr> <int> #> 1 en 40736 #> 2 es 447 #> 3 en/eo 19 #> 4 en/la 19 #> 5 en/es 13 #> 6 en/fr 13 #> 7 de/en 7 #> 8 ang/en 3 #> 9 cy/en 3 #> 10 en/enm 3 #> # … with 20 more rows