The avatar for @artistes-femmes-mac
Artistes femmes dans la collection du MAC (1964-2020)
Mémoire de maîtrise de Valentine Desmorat (en cours) « L'entrée des femmes artistes dans la collection du Musée d'art contemporain, de 1964 à nos jours : analyse statistique et facteurs déterminants » Co-créations avec Lena Krause
Public
HTMlles2024
Edited
Jun 1, 2023
Fork of Nombres d'achats/dons/acquisitions d'œuvres d'artistes-femmes et d'œuvres d'artistes-hommes par année (1964-2020)
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
genres = new Set(oeuvresMacEtudiees.map(d => d.genreAssocie))
Insert cell
categories = new Set(oeuvresMacEtudiees.map( d => d.categorie))
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
oeuvresMac.find(d => d.id =="dualite-dualite")
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
oeuvreSansArtiste = oeuvresMac.find(d => d.title ="New York Stock Exchange")
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
Insert cell
import {oeuvresTri3Categories} from "1cd6c83a4402c258"
Insert cell
import {oeuvresMacEtudiees} from "1cd6c83a4402c258"
Insert cell
import {associationGenreAOeuvre} from "1cd6c83a4402c258"
Insert cell
import {artistesMac} from "1cd6c83a4402c258"
Insert cell
import {oeuvresMac} from "1cd6c83a4402c258"
Insert cell
import {couleurs} from "26cecfbef9723965"
Insert cell
jaune = couleurs[0]
Insert cell
noir = couleurs[3]
Insert cell
bordeau = couleurs[2]
Insert cell
gris = couleurs[1]
Insert cell
import {interval} from '@mootari/range-slider@1781'
Insert cell
Insert cell

One platform to build and deploy the best data apps

Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.
Learn more