30:[{"id":"47b4d5a4f045373ad59312cc940aa53c72e0972c4baf1c69089ac3e527fb34ecba11d80b0b294df78649a7ae7c72beecbe2bdac31fac5b501a2edfece853f29c","href":"https://static.observableusercontent.com/files/47b4d5a4f045373ad59312cc940aa53c72e0972c4baf1c69089ac3e527fb34ecba11d80b0b294df78649a7ae7c72beecbe2bdac31fac5b501a2edfece853f29c","name":"fullData.csv","type":"text/csv","lastModified":1620316810742.693,"size":724683},{"id":"a7062daaefa3ef153a0ef0f92006e040fba3bf116de731cef2775a00cd2408857e6a3f64715f805e94d6f22670a54b629c664476eb8fd27124ac735ce85e4aac","href":"https://static.observableusercontent.com/files/a7062daaefa3ef153a0ef0f92006e040fba3bf116de731cef2775a00cd2408857e6a3f64715f805e94d6f22670a54b629c664476eb8fd27124ac735ce85e4aac","name":"edadXmesa-csv.csv","type":"text/csv","lastModified":1620331766321.164,"size":601049},{"id":"2de8d8ad120a8cadcddacb68b6e72b5f920ce482052b4948ed145fd3213b763d255f22179f2a3f1e1417cacd19420e3d001d7a0757a726a85e4bd97d96d9963a","href":"https://static.observableusercontent.com/files/2de8d8ad120a8cadcddacb68b6e72b5f920ce482052b4948ed145fd3213b763d255f22179f2a3f1e1417cacd19420e3d001d7a0757a726a85e4bd97d96d9963a","name":"mixedData-2.csv","type":"text/csv","lastModified":1620285536712.525,"size":431917}] 2e:{"title":" Probando Plot","cells":[{"id":0,"value":"md`# Probando Plot`","pinned":false,"hidden":false,"mode":"ojs"},{"id":183,"value":"html`

% de votos que recibió cada bloque según la renta media de la sección censal

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Por un lado, en azul: Cs, PP y Vox; y por el otro, en rojo: Más Madrid, PSOE y Unidas Podemos

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":103,"value":"Plot.plot({\n y: { tickFormat: \".0%\", label: \"↑ %Voto\" },\n x: {\n tickFormat: (d) => d.toLocaleString(\"de-DE\") + \"€\",\n label: \"ingresos anuales por hogar →\"\n },\n grid: true,\n color: {\n domain: [\"dcha\", \"izq\"],\n range: [\"#19A8E9\", \"#E52121\"]\n },\n //width: width,\n marks: [\n Plot.ruleY([0.5], { strokeOpacity: 0.3 }),\n Plot.dot(longData, {\n x: \"renta\",\n y: \"perc\",\n fill: \"bloque\",\n fillOpacity: 0.7,\n r: 1.8\n })\n ],\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":288,"value":"Plot.plot({\n y: { tickFormat: \".0%\", label: \"↑ %Voto\" },\n x: {\n label: \"ingresos anuales por hogar →\",\n nice: true,\n tickFormat: (d) => d.toLocaleString(\"de-DE\") + \"€\"\n },\n fx: {\n label: null\n },\n grid: true,\n color: {\n domain: [\"dcha\", \"izq\"],\n range: [\"#19A8E9\", \"#E52121\"]\n },\n facet: {\n data: longData,\n x: \"bloque\"\n },\n //width: width,\n marks: [\n Plot.ruleY([0.5], { strokeOpacity: 0.3 }),\n Plot.frame(),\n Plot.dot(longData.slice(), {\n x: \"renta\",\n y: \"perc\",\n r: 1.8,\n fillOpacity: 0.4,\n fill: \"#ddd\"\n }),\n Plot.dot(longData, {\n x: \"renta\",\n y: \"perc\",\n fill: \"bloque\",\n fillOpacity: 0.4,\n r: 1.8\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":455,"value":"html`

Nº de votos que recibió cada partido según la renta media de la sección censal

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Dentro de cada bloque también se puede ver la diferencia de votos que ha recibido cada partido según la renta

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":379,"value":"Plot.plot({\n y: { label: \"↑ Nº votos\" },\n x: {\n label: \"ingresos anuales por hogar →\",\n nice: true,\n tickFormat: (d) => d.toLocaleString(\"de-DE\") + \"€\"\n },\n fy: {\n label: null\n },\n grid: true,\n color: {\n domain: [\"PP\", \"Vox\", \"Cs\", \"PSOE\", \"Unidas Podemos\", \"Más Madrid\"],\n range: [\"#19A8E9\", \"#AAD756\", \"#fc8d62\", \"#E52121\", \"#7C3E80\", \"#66c2a5\"]\n },\n facet: {\n data: fullData,\n y: \"partido\",\n marginRight: 90\n },\n //width: width,\n marks: [\n Plot.ruleY([0.5], { strokeOpacity: 0.3 }),\n Plot.frame(),\n Plot.dot(fullData.slice(), {\n x: \"renta\",\n y: \"votos\",\n r: 1.8,\n fillOpacity: 0.1,\n fill: \"#ddd\"\n }),\n Plot.dot(fullData, {\n x: \"renta\",\n y: \"votos\",\n fill: \"partido\",\n fillOpacity: 0.4,\n r: 1.8\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":461,"value":"html`

Nº de votos que recibió cada partido según la edad media de la sección censal

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":472,"value":"html`

Y según la edad

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":447,"value":"Plot.plot({\n y: { label: \"↑ Nº votos\", tickFormat: (d) => d.toLocaleString(\"de-DE\") },\n x: {\n label: \"edad →\",\n nice: true\n },\n fy: {\n label: null\n },\n grid: true,\n color: {\n domain: [\"PP\", \"Vox\", \"Cs\", \"PSOE\", \"UP\", \"MM\"],\n range: [\"#19A8E9\", \"#AAD756\", \"#fc8d62\", \"#E52121\", \"#7C3E80\", \"#66c2a5\"]\n },\n facet: {\n data: edadData,\n y: \"partido\"\n },\n //width: width,\n marks: [\n Plot.ruleY([0.5], { strokeOpacity: 0.3 }),\n Plot.frame(),\n Plot.dot(edadData.slice(), {\n x: \"edad\",\n y: \"votos\",\n r: 1.8,\n fillOpacity: 0.1,\n fill: \"#ddd\"\n }),\n Plot.dot(edadData, {\n x: \"edad\",\n y: \"votos\",\n fill: \"partido\",\n fillOpacity: 0.4,\n r: 1.8\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":202,"value":"// data","pinned":true,"hidden":false,"mode":"ojs"},{"id":159,"value":"longData = FileAttachment(\"mixedData-2.csv\").csv({ typed: true })","pinned":false,"hidden":false,"mode":"ojs"},{"id":378,"value":"fullData = FileAttachment(\"fullData.csv\").csv({ typed: true })","pinned":false,"hidden":false,"mode":"ojs"},{"id":441,"value":"edadData = FileAttachment(\"edadXmesa-csv.csv\").csv({ typed: true })","pinned":false,"hidden":false,"mode":"ojs"},{"id":200,"value":"// librerías","pinned":true,"hidden":false,"mode":"ojs"},{"id":99,"value":"Plot = require(\"@observablehq/plot@0.1\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":155,"value":"import { swatches as Swatches } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":165,"value":"import { tweet } from \"@mbostock/tweet\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W30","stdlib":"1","titling":"auto"}