31:T79f,chart = { const svg = d3.create("svg") .attr("viewBox", [0, 0, width, height]); const {nodes, links} = sankey(data); svg.append("g") .attr("stroke", "#000") .selectAll("rect") .data(nodes) .join("rect") .attr("x", d => d.x0) .attr("y", d => d.y0) .attr("height", d => d.y1 - d.y0) .attr("width", d => d.x1 - d.x0) .attr("fill", color) .append("title") .text(d => `${d.name}\n${format(d.value)}`); const link = svg.append("g") .attr("fill", "none") .attr("stroke-opacity", 0.5) .selectAll("g") .data(links) .join("g") .style("mix-blend-mode", "multiply"); if (edgeColor === "path") { const gradient = link.append("linearGradient") .attr("id", d => (d.uid = DOM.uid("link")).id) .attr("gradientUnits", "userSpaceOnUse") .attr("x1", d => d.source.x1) .attr("x2", d => d.target.x0); gradient.append("stop") .attr("offset", "0%") .attr("stop-color", d => color(d.source)); gradient.append("stop") .attr("offset", "100%") .attr("stop-color", d => color(d.target)); } link.append("path") .attr("d", d3.sankeyLinkHorizontal()) .attr("stroke", d => edgeColor === "none" ? "#aaa" : edgeColor === "path" ? d.uid : edgeColor === "input" ? color(d.source) : color(d.target)) .attr("stroke-width", d => Math.max(1, d.width)); link.append("title") .text(d => `${d.source.name} → ${d.target.name}\n${format(d.value)}`); svg.append("g") .attr("font-family", "sans-serif") .attr("font-size", 10) .selectAll("text") .data(nodes) .join("text") .attr("x", d => d.x0 < width / 2 ? d.x1 + 6 : d.x0 - 6) .attr("y", d => (d.y1 + d.y0) / 2) .attr("dy", "0.35em") .attr("text-anchor", d => d.x0 < width / 2 ? "start" : "end") .text(d => d.name); return svg.node(); }32:T4d9,viewof prov_elegida = Object.assign(html``)33:T42c,viewof view2 = embed( { "$schema": "https://vega.github.io/schema/vega-lite/v4.json", "data": { "values": nac.filter(l => l['AÑO'] == anos && l['PROVNAME'] == prov_elegida) }, "selection": { "highlight": {"type": "single"} }, "mark": {"type": "rect", "strokeWidth": 2}, "encoding": { "y": { "field": "ITIEMGEST", "type": "nominal" }, "x": { "field": "IMEDAD", "type": "nominal" }, "fill": { "field": "CUENTA", "aggregate": "sum", "type": "quantitative" }, "stroke": { "condition": {"test": {"and": [{"selection": "highlight"}, "length(data(\"highlight_store\"))"]}, "value": "black"}, "value": null }, "opacity": { "condition": {"selection": "highlight", "value": 1}, "value": 0.2 } }, "config": { "scale": { "bandPaddingInner": 0, "bandPaddingOuter": 0 }, "view": {"step": 40}, "range": { "ramp": { "scheme": "yellowgreenblue" } }, "axis": { "domain": false } } } ) 34:[] 2f:{"title":"Nacimientos Argentina 2005-2018","cells":[{"id":0,"value":"md`# Nacimientos Argentina 2005-2018\nPara visualizar correctamente los graficos, darle play a las celdas.`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2,"value":"import { vl } from \"@vega/vega-lite-api\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":93,"value":"md`## Carga de Datos`","pinned":false,"hidden":false,"mode":"ojs"},{"id":10,"value":"url = \"https://fsammart.github.io/public/info-vis/tp-nacimientos/\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":209,"value":"nacimientos = {\n var nac18 = d3.csv( url + 'NacWeb18.csv');\n var nac17 = d3.csv( url + 'NacWeb17.csv');\n var nac16 = d3.csv( url + 'NacWeb16.csv');\n var nac15 = d3.csv( url + 'NacWeb15.csv');\n var nac14 = d3.csv( url + 'NacWeb14.csv');\n var nac13 = d3.csv( url + 'NacWeb13.csv');\n var nac12 = d3.csv( url + 'NacWeb12.csv');\n var nac11 = d3.csv( url + 'NacWeb11.csv');\n var nac10 = d3.csv( url + 'NacWeb10.csv');\n var nac09 = d3.csv( url + 'NacWeb09.csv');\n var nac08 = d3.csv( url + 'NacWeb08.csv');\n var nac07 = d3.csv( url + 'NacWeb07.csv');\n var nac06 = d3.csv( url + 'NacWeb06.csv');\n var nac05 = d3.csv( url + 'NacWeb05.csv');\n return {\n nac05: await nac05,\n nac06: await nac06,\n nac07: await nac07,\n nac08: await nac08,\n nac09: await nac09,\n nac10: await nac10,\n nac11: await nac11,\n nac12: await nac12,\n nac13: await nac13,\n nac14: await nac14,\n nac15: await nac15,\n nac16: await nac16,\n nac17: await nac17,\n nac18: await nac18\n }\n }","pinned":false,"hidden":false,"mode":"ojs"},{"id":204,"value":"{\n nacimientos.nac05.map(l => {l['AÑO'] = \"2005\"; return l})\n nacimientos.nac06.map(l => {l['AÑO'] = \"2006\"; return l})\n nacimientos.nac07.map(l => {l['AÑO'] = \"2007\"; return l})\n nacimientos.nac08.map(l => {l['AÑO'] = \"2008\"; return l})\n nacimientos.nac09.map(l => {l['AÑO'] = \"2009\"; return l})\n nacimientos.nac10.map(l => {l['AÑO'] = \"2010\"; return l}) \n nacimientos.nac11.map(l => {l['AÑO'] = \"2011\"; return l}) \n nacimientos.nac12.map(l => {l['AÑO'] = \"2012\"; return l}) \n nacimientos.nac13.map(l => {l['AÑO'] = \"2013\"; return l}) \n nacimientos.nac14.map(l => {l['AÑO'] = \"2014\"; return l})\n nacimientos.nac15.map(l => {l['AÑO'] = \"2015\"; return l}) \n nacimientos.nac16.map(l => {l['AÑO'] = \"2016\"; return l})\n nacimientos.nac17.map(l => {l['AÑO'] = \"2017\"; return l})\n nacimientos.nac18.map(l => {l['AÑO'] = \"2018\"; return l}) \n \n} ","pinned":false,"hidden":false,"mode":"ojs"},{"id":323,"value":"nac =nacimientos.nac05.concat(nacimientos.nac06,nacimientos.nac07,nacimientos.nac08,nacimientos.nac09,nacimientos.nac10,nacimientos.nac11,nacimientos.nac12,nacimientos.nac13,nacimientos.nac14,nacimientos.nac15,nacimientos.nac16,nacimientos.nac17,nacimientos.nac18)","pinned":false,"hidden":false,"mode":"ojs"},{"id":543,"value":"nac[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":364,"value":"provvscode = ({\n 2: 'CABA',\n 6: 'Buenos Aires',\n 10: 'Catamarca',\n 14: 'Córdoba',\n 18: 'Corrientes',\n 22: 'Chaco',\n 26: 'Chubut',\n 30: 'Entre Rios',\n 34: 'Formosa',\n 38: 'Jujuy',\n 42: 'La Pampa',\n 46: 'La Rioja',\n 50: 'Mendoza',\n 54: 'Misiones',\n 58: 'Neuquen',\n 62: 'Rio Negro',\n 66: 'Salta',\n 70: 'San Juan',\n 74: 'San Luis',\n 78: 'Santa Cruz',\n 82: 'Santa Fe',\n 86: 'Santiago del Estero',\n 90: 'Tucumán',\n 94: 'Tierra del Fuego',\n})\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":369,"value":"nac.map(l => {\n l[\"PROVNAME\"] = provvscode[Number(l.PROVRES)] ;\n let aux = poblacion_provincias.find(x => x['Codigo'] == l.PROVRES);\n if(aux !== undefined){\n l[\"POBLACION_PROVINCIA\"] = aux['Población'];\n l['PORCENTAJE'] = Number(l['CUENTA'])/Number(aux['Población']);\n return l\n }\n return null\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":91,"value":"md`## Graficos asociados`","pinned":false,"hidden":false,"mode":"ojs"},{"id":107,"value":"md`### Cantidad de Partos por Provincias`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":537,"value":"viewof ano = Object.assign(html``)","pinned":false,"hidden":false,"mode":"ojs"},{"id":97,"value":"vl.markBar() // Make a bar chart\n .data(nac.filter(x => x['PROVNAME'] !== undefined && x['AÑO'] == ano )) // With the cars data again\n .encode(\n vl.y().fieldN(\"PROVNAME\").sort('-x').title(\"Provincias\"), // y can come before x: different orders won't break anything\n vl.x().sum(\"PORCENTAJE\").title(\"Partos\") // For x, count the number of records\n )\n .render() // Draw the chart","pinned":false,"hidden":false,"mode":"ojs"},{"id":617,"value":"md`Se puede ver que la provincia Misiones, en la mayoría de los años, lidera la lista de partos sobre población. Es interesante destacar que CABA, siempre se encuentra última, esto puede deberse a la gran concentración de población con respecto a las demás provincias.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":465,"value":"poblacion_provincias = d3.tsv('https://gist.githubusercontent.com/aaizemberg/0fdac29e4b2b9e0c245abd6731de8e2c/raw/04db0b956351c88596bc2f5300cc18d8a7667fb1/provincias.tsv')","pinned":false,"hidden":false,"mode":"ojs"},{"id":110,"value":"md`### Sankey Provincias y Nivel de Estudios de Madre`","pinned":false,"hidden":false,"mode":"ojs"},{"id":112,"value":"viewof edgeColor = Object.assign(html``, {\n value: new URLSearchParams(html``.search).get(\"color\") || \"path\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":115,"value":"viewof size = Object.assign(html``, {\n value: new URLSearchParams(html``.search).get(\"size\") || \"10\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":117,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":99,"value":"sankey = {\n const sankey = d3.sankey()\n .nodeId(d => d.name)\n .nodeWidth(15)\n .nodePadding(10)\n .extent([[1, 5], [width - 1, height - 5]]);\n return ({nodes, links}) => sankey({\n nodes: nodes.map(d => Object.assign({}, d)),\n links: links.map(d => Object.assign({}, d))\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":120,"value":"format = {\n const format = d3.format(\",.0f\");\n return data.units ? d => `${format(d)} ${data.units}` : format;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":122,"value":"color = {\n const color = d3.scaleOrdinal(d3.schemeCategory10);\n return d => color(d.category === undefined ? d.name : d.category);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":124,"value":"data = {\n const data = nac.map(function(d) {\n return {\n source: d.PROVNAME,\n target: d.IMINSTRUC,\n value: d.PORCENTAJE\n }\n});;\n const links = data.slice(0, size);\n const nodes = Array.from(new Set(links.flatMap(l => [l.source, l.target])), name => ({name, category: name.replace(/ .*/, \"\")}));\n return {nodes, links, units: \"cantidad\"};\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":126,"value":"width = 954","pinned":false,"hidden":false,"mode":"ojs"},{"id":128,"value":"height = 600","pinned":false,"hidden":false,"mode":"ojs"},{"id":621,"value":"md`Algo relevante del diagrama Sankey es que muestra que la mayor parte de los partos en Buenos Aires se da en madres con educación primaria, mientras que en CABA, la educación de las madres es en su mayoría secundaria. Esto podría deberse a una mayor educación sexual en CABA.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":402,"value":"md `### Heat Map Edad de la Madre con Tiempo de Gestación\n\nSe mostrará el heat map por años.`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":586,"value":"viewof anos = Object.assign(html``)","pinned":false,"hidden":false,"mode":"ojs"},{"id":623,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":578,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":627,"value":"md`Es interesante notar que CABA, a lo largo de todos los años analizados, es la provincia cuyo promedio de edad de gestantes es la mayor. Nuevamente creemos que un factor asociado a ello podría ser la educación sexual, el acceso a métodos anticonceptivos.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":410,"value":"embed = require(\"vega-embed@6\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":425,"value":"picasso = require(\"picasso.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":601,"value":"d3 = require(\"d3@5\", \"d3-sankey@0.12\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}