| artists {arthistory} | R 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")