Public
Edited
Mar 7
3 stars
library = import("https://cdn.jsdelivr.net/npm/d3@7/+esm")
library2 = import("https://cdn.jsdelivr.net/npm/d3@6/+esm")
d3 = require("d3@6.7.0/dist/d3.min.js")
import {Scrubber} from "@mbostock/scrubber"
viz = require("geoviz@0.7.9")
dataallyears = FileAttachment("data-allyears.csv").csv({ typed: true })
pays = FileAttachment("world.geojson").json()
data-allyears.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
minyear = d3.min(dataallyears, (d) => d.year)
maxyear = d3.max(dataallyears, (d) => d.year)
year = d3.range(minyear, maxyear + 1, 1);
normalizeGDP = (gdpValue) => (gdpValue - mingdp) / (maxgdp - mingdp)
normalizedData = dataallyears
.filter(d => d.gdp != null) // Filtrer les objets où 'gdp' n'est pas null ou undefined
.map(d => ({
...d, // Garder toutes les autres propriétés
normalized_gdp: normalizeGDP(d.gdp) * 100 // Ajouter la valeur 'normalized_gdp'
}));
Inputs.table(normalizedData)
dataallyearsworld_merge = viz.tool.merge({
geom: pays,
geom_id: "ISO3", // Accès correct à l'ISO3 dans properties
data: normalizedData,
data_id: "id"
});
dataallyearsworld = dataallyearsworld_merge.featureCollection
dataallyears2000 = dataallyears
.filter(d => d.year === 2000 && d.genre != null);
dataallyears2020 = dataallyears
.filter(d => d.year === 2020 && d.genre != null);
dataallyearsworld2000_merge = viz.tool.merge({
geom: pays,
geom_id: "ISO3",
data: dataallyears2000,
data_id: "id"
});
dataallyearsworld2020_merge = viz.tool.merge({
geom: pays,
geom_id: "ISO3",
data: dataallyears2020,
data_id: "id"
});
dataallyearsworld2000 = dataallyearsworld2000_merge.featureCollection
dataallyearsworld2020 = dataallyearsworld2020_merge.featureCollection
dataallyearsfilter = normalizedData.filter(d => d.year === date );
data_filter_merge = viz.tool.merge({
geom: pays,
geom_id: "ISO3", // Accès correct à l'ISO3 dans properties
data: dataallyearsfilter,
data_id: "id"
});
data_filter = data_filter_merge.featureCollection
mingdp = d3.min(dataallyears, (d) => d.gdp)
maxgdp = d3.max(dataallyears, (d) => d.gdp)
dataallyearsfilter1 = normalizedData.filter(d => d.year === years9);
data_edudep_merge = viz.tool.merge({
geom: pays,
geom_id: "ISO3", // Accès correct à l'ISO3 dans properties
data: dataallyearsfilter1,
data_id: "id"
});
data_edupchoro_filter = data_edudep_merge.featureCollection
// Grouper les données par pays et calculer les moyennes
groupedData2 = d3.rollup(
normalizedData, // Utilisation des données où les moyennes sont déjà ajoutées
v => ({
MoyennePubli: d3.mean(v.map(d => +d.publi).filter(d => d != null)) || 0,
MoyenneRd: d3.mean(v.map(d => +d.rd).filter(d => d != null)) || 0
}),
d => d.id
);
// Convertir la Map en tableau d'objets avec seulement les 3 colonnes demandées
tab = Array.from(groupedData2, ([id, moyennes]) => ({
id,
MoyennePubli: moyennes.MoyennePubli,
MoyenneRd: moyennes.MoyenneRd
}));
Inputs.table(tab)
tab_merge = viz.tool.merge({
geom: pays,
geom_id: "ISO3", // Accès correct à l'ISO3 dans properties
data: tab,
data_id: "id"
});
tab_choroprop = tab_merge.featureCollection
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