artists: Artists by edition of Gardner or Janson's art history...

artistsR Documentation

Artists by edition of Gardner or Janson's art history textbook

Description

Artists by edition of Gardner or Janson's art history textbook

Usage

artists

Format

A data frame with 3,162 observations on 14 variables.

artist_name

The name of the artist.

edition_number

The number of the edition of either Gardner's Art Through the Ages or Janson's History of Art.

year

The year of publication.

artist_nationality

The nationaliity of the artist.

artist_nationality_other

The nationality of the artist. Of the total count of artists through all editions of Gardner's Art Through the Ages and Janson's History of Art, 77.32% account for French, Spanish, British, American and German. Therefore, the categorical strings of this variable are French, Spanish, British, American, German and Other.

artist_gender

The gender of the artist.

artist_race

The race of the artist.

artist_ethnicity

The ethnicity of the artist.

book

Which book, either Janson or Gardner the particular artist at that particular time was included.

space_ratio_per_page_total

The area in centimeters squared of both the text and the figure of a particular artist in a given edition of Janson's History of Art or Gardner's Art Through the Ages divided by the area in centimeters squared of a single page of the respective edition.

artist_unique_id

A unique identifying number assigned to artists across books and editions denoted in alphabetical order.

moma_count_to_year

The count of exhibitions held by the Museum of Modern Art (MoMA) of a particular artist at a particular moment of time, as highlighted by year.

whitney_count_to_year

The count of exhibitions held by The Whitney of a particular artist at a particular moment of time, as highlighted by year.

artist_race_nwi

The non-white indicator for artist race, meaning if an artist's race is denoted as either white or non-white.

Source

Stam, H. (2022). Quantifying art historical narratives. doi: 10.7924/r4dn48h0w. Duke Research Data Repository.

Examples

library(ggplot2)
library(dplyr)

artists %>%
ggplot(aes(y = book , fill = artist_gender))+
 geom_bar()+
 labs(
   title = "Gender by Book",
   x = "Count of Artists",
   y = "Book",
   fill = "Artist Gender")

saralemus7/arthistory documentation built on June 1, 2022, 8:19 a.m.