Published
Edited
Nov 6, 2020
1 star
candidaturas = d3.csvParse(await FileAttachment("candidaturas-2020.csv").text(), d3.autoType);
dataMap = new Map(candidaturas.map(d => [codigos.get(d.sigla_ue), d]));
dataMap.get(1301654).nao_brancos
fillScalePop = {
const values = [... dataMap.values()].map(d => d.nao_brancos);
return d3.scaleSequential(d3.extent(values), d3.interpolateCividis).nice();
}
mapaBR = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
svg.append("g")
.selectAll("path")
.data(topojson.feature(br, br.objects.Munic).features)
.join("path")
.attr("stroke", "none")
.attr("fill", d => dataMap.has(d.id) ? fillScalePop(dataMap.get(d.id).nao_brancos) : "#ddd")
.attr("d", pathBR)
.append("title")
.text(d => tooltipCP(d))
// legenda
svg.append("g")
.attr("transform", "translate(410,20)")
.append(() => legend({color: fillScalePop,
title: "Proporção dos candidatos que não são brancos.",
width: 250,
tickFormat: ",%"}));
return svg.node();
}
dadosPontosPB = {
const gjFeatureMap = new Map(topojson.feature(pb, pb.objects.Munic).features.map(d => [d.id, d]));
const dados = candidaturas.filter(d => d.sigla_uf === "PB").map(({codigo_ibge, nao_brancos, candidaturas, nome_municipio, capital}) => {
const feature = gjFeatureMap.get(codigo_ibge);
return{
codigo_ibge,
nao_brancos,
candidaturas,
nome_municipio,
capital,
posicao : feature && pathGenPB.centroid(feature) // <-- Repare aqui
};
})
return dados.filter(d => d.posicao);
}
radiusScale = d3.scaleSqrt([1, d3.max(dadosPontosPB, d => d.candidaturas)], [0, 20])
fillPointsScale = d3.scaleSequential([0, 1], d3.interpolatePuOr).nice()
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
