2e:null 2f:["$","title",null,{"children":"Cundinamarca - Colombia 2017 | monicamarcelac | Observable"}] 34:Td8d,md`# Cundinamarca - Colombia 2017

*Analysis about the relationship between crime and demographic variables*

Este proyecto usa como fuentes de datos los [delitos reportados en los 116 municipios de Cundinamarca](https://mapasyestadisticas-cundinamarca-map.opendata.arcgis.com/datasets/0981a0e44ec243508ab1886eeb324416_0/data?page=2) y la composición de la [pirámide poblacional](https://mapasyestadisticas-cundinamarca-map.opendata.arcgis.com/datasets/pir%C3%A1mide-poblaci%C3%B3n-2017) del mismo departamento, utilizando para los dos sets la información del año 2017.

El análisis busca encontrar las relaciones entre estas variable que han reportado algunos estudios, tanto en el área de la sociología como en el área de la economía, especificamente de economía del crimen [(Bonilla Mejía: Demografía, juventud y homicidios en Colombia, 1979-2006)](http://www.banrep.gov.co/docum/Lectura_finanzas/pdf/DTSER-118.pdf). En estos, se destacan como variables principales la comoposición demográfica, el desempleo, la desigualdad y las efectividad de la policía. Sin embargo, para el desarrollo de este proyecto solo se tendrán en cuenta las variables demográficas.

A continuación se describen los detalles del proyecto:

* \`Objetivo: Encontrar, si existen, las posibles relaciones entre la composición demográfica de los municipios de Cundinamarca y los delitos reportados en los mismos. \` * \`Tecnologías usadas: Para el procesamiento de la información se utilizó Alteryx Designer 2018.2, repositorio de información final GitHub, análisis exploratorio Power BI, desarrollo de visualización final d3 (Observable)\` * \`Forma de consulta: Se debe ingresar por medio del link que dirige al notebook en Observable \`

**Utilice los filtros disponbible a lo largo del notebook para explorar y utilizar las visualizaciones de forma adecuada**

**Créditos y fuentes usadas**

[Inputs](https://beta.observablehq.com/@jashkenas/inputs) - Jeremy Ashkenas

[Tables](https://beta.observablehq.com/@tmcw/tables) - Tom MacWright

[Scatter plot +](https://beta.observablehq.com/@tippytappy/scatter-plot) - Dylan Omran

[Bar Chart](https://beta.observablehq.com/d/d01bc5e50aa77080) - John Alexis Guerra Gómez

[Learning D3.js Donut Chart in Observable](https://beta.observablehq.com/@aaronkyle/learning-a-donut-chart-from-d3-js) - Aaron Kyle Dennis

` 35:T9d6,chart = { const height = 300, margin = {left:6, right:1, top: 7, bottom:5}, iwidth = width - margin.left -margin.right, iheight = height - margin.top - margin.bottom; const svg = d3.select(DOM.svg(w, h)); // define the X Axis var xAxis = d3.axisBottom() .tickFormat(d3.format(",")) .scale(xs); var formatComma = d3.format(",") // define the Y axis var yAxis = d3.axisLeft() .scale(ys); const g = svg.append("g") .attr("transform", `translate(${margin.left},${margin.top})`) let tooltip ; // draw the X axis g.append("g") .attr("transform", "translate(0," + (h - padding) + ")") .call(xAxis); // draw the Y axis g.append("g") .attr("transform", "translate(" + padding + ",0)") .call(yAxis); ///// labels and legends ///// // text label for the x axis g.append("text") .text(xName) .style("text-anchor", "middle") .style("font-size", 12) .attr("font-family", "sans-serif") .attr("transform", "translate(90, 380)"); // text label for the y axis g.append("text") .text(yName) .style("text-anchor", "left") .style("font-size", 12) .attr("font-family", "sans-serif") .attr("transform", "translate(0, 40)"); // create the circles g.selectAll("circles") .data(delitos_poblacion) .enter() .append("circle") .attr("cx", d => xs(d[xName])) .attr("cy", d => ys(d[yName])) .attr("r", 8) .style("fill", "#FF8C94") .style("stroke", "white") .style("stroke-width", .6) .on("mouseover", function (d) { console.log(d); d3.select(this) .style("fill", "#A9C6CF") tooltip .attr("x", xs(d[xName])) .attr("y", ys(d[yName]) - 10) .style("display", "block") .text(function() { return `Municipio : ${d.Municipio} `+ xName + ' : ' + formatComma(d[xName]) + ' '+ yName + ' : ' + formatComma(d[yName]); }); }) .on("mouseout", function(d, i) { console.log(d); d3.select(this) .style("fill", "#FF8C94") tooltip.hide .attr("x", xs(d[xName])) .attr("y", ys(d[yName]) - 15) .style("fill", "none") }); tooltip = g.append("text") .style("font-size", "8pt") .style("font-family", "sans-serif") .style("color", "steelblue") .attr("x", -10); return svg.node(); }36:T4e2,Donut_char = { var width = 460, height = 300, radius = Math.min(width, height) / 2; var color = d3.scaleOrdinal() .range(["#6CA4A7", "#F0DFA7", "#7D7A7A", "#C18265", "#995D6B", "#243F45", "#2DAAA7"]); var arc = d3.arc() .outerRadius(radius - 20) .innerRadius(radius - 70); var pie = d3.pie() .sort(null) .value(function(d) { return d.Sum_Total_Delitos; }); var container = html``; var svg = d3.select(container) .attr("width", width) .attr("height", height) .append("g") .attr("transform", "translate(" + width / 2 + "," + height / 2 + ")"); var format = d3.format(".2n") var share = d => d.Share var g = svg.selectAll(".arc") .data(pie(delitos_group)) .enter().append("g") .attr("class", "arc"); g.append("path") .attr("d", arc) .attr("fill", function(d) { return color(d.data.Delito); }); g.append("text") .attr("transform", function(d) { return "translate(" + arc.centroid(d) + ")"; }) .attr("dy", ".55em") .text(function(d) { return d.data.Delito + " "+ format(d.data.Share) +"%"; }) .style("font-family", "sans-serif") .style("font-size", "10pt"); return container; }37:T6a9,barchart_Otros ={ // var data4 = data3.sort( (a,b) => d3.descending(a.value, b.value)); var height = 300, margin = {top: 20, right: 20, bottom: 40, left: 50}, iwidth = width - margin.left - margin.right, iheight = height - margin.top - margin.bottom, svg = d3.select(DOM.svg(width, height)), g=svg .append("g") .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); var format = d3.format(",.2%") var color = d3.scaleOrdinal() .range(["#6CA4A7", "#F0DFA7", "#7D7A7A", "#C18265", "#995D6B", "#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"]); const filteredData = OtrosDelitos .sort( (a, b) => d3.descending(a.Total_Delitos, b.Total_Delitos) ) .slice(0,SelectNcrime); const y = d3.scaleLinear() .domain([0, d3.max(filteredData, d=> d.Total_Delitos)]) .range([iheight, 0]); const x = d3.scaleBand() .padding(0.1) .domain(OtrosDelitos.slice(0,SelectNcrime) .map( d => d.Delito) ) .range([0, iwidth]); var bar=g.selectAll("rect") .data(OtrosDelitos) .enter() .append("rect") .attr("class", "bar") .attr("x", d => x(d.Delito)) .attr("y", d => y(d.Total_Delitos)) .attr("height", d => y(0) - y(d.Total_Delitos)) .attr("width", x.bandwidth()) .attr("fill", "#F0DFA7"); g.append("g") .attr("class", "x axis") .attr("transform", `translate(0,${iheight})`) .call(d3.axisBottom(x)); g.append("g") .attr("class", "y axis") .call(d3.axisLeft(y)); return svg.node(); }38:T54e,ShareOtros = { var width = 460, height = 300, radius = Math.min(width, height) / 2; var color = d3.scaleOrdinal() .range(["#6CA4A7", "#F0DFA7", "#7D7A7A", "#C18265", "#995D6B", "#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"]); var arc = d3.arc() .outerRadius(radius - 20) .innerRadius(radius - 70); var pie = d3.pie() .sort(null) .value(function(d) { return d.Total_Delitos; }); var container = html``; var svg = d3.select(container) .attr("width", width) .attr("height", height) .append("g") .attr("transform", "translate(" + width / 2 + "," + height / 2 + ")"); var format = d3.format(",.2%") var share = d => d.Total_Delitos var g = svg.selectAll(".arc") .data(pie(OtrosDelitos)) .enter().append("g") .attr("class", "arc"); g.append("path") .attr("d", arc) .attr("fill", function(d) { return color(d.data.Delito); }); g.append("text") .attr("transform", function(d) { return "translate(" + arc.centroid(d) + ")"; }) .attr("dy", ".55em") .text(function(d) { return d.data.Delito + " "+ d.data.Share +"%"; }) //.text(function(d) { return d.data.Share +"%"; }) .style("font-family", "sans-serif") .style("font-size", "7pt"); return container; }39:T5bb,barchart ={ // var data4 = data3.sort( (a,b) => d3.descending(a.value, b.value)); var height = 400, margin = {top: 20, right: 20, bottom: 50, left: 120}, iwidth = width - margin.left - margin.right, iheight = height - margin.top - margin.bottom, svg = d3.select(DOM.svg(width, height)), g=svg .append("g") .attr("transform", "translate(" + margin.left + "," + margin.top + ")"); const filteredData = dataset .sort( (a, b) => d3.descending(a.Total_Delitos, b.Total_Delitos) ) .slice(0,SelectNtown); const x = d3.scaleLinear() .domain([0, d3.max(filteredData, d=> d.Total_Delitos)]) .range([0, iwidth]); const y = d3.scaleBand() .padding(0.1) .domain(dataset.slice(0,SelectNtown) .map( d => d.Municipio) ) .range([0, iheight]); var bar=g.selectAll("rect") .data(filteredData) .enter() .append("rect") .attr("class", "bar") .attr("x", 0 ) .attr("width", function(d){ return x(d.Total_Delitos); }) .attr("y", function(d){ return y(d.Municipio); }) .attr("height", y.bandwidth()) .attr("fill", "#995D6B"); g.append("g") .attr("class", "x axis") .attr("transform", `translate(0,${iheight})`) .call(d3.axisBottom(x)); g.append("g") .attr("class", "y axis") .call(d3.axisLeft(y)); return svg.node(); }3a:T528,viewof Correlation_Table = { let t = table(dataCorr, { columns: { name: { formatter(value, i, row) { let elem = html`${value}`; elem.addEventListener('click', () => { t.value = row; t.dispatchEvent(new CustomEvent('input')); }); return elem; } }, "All Data": { formatter(val, i) { let color = d3.scaleLinear() .domain([-0.2, 0, 0.3]) .range(["#f4c8cf", "#f8f8f8", "#c8f4cb"]); return html`${val}`; } }, Top50: { formatter(val, i) { let color = d3.scaleLinear() .domain([-0.2, 0, 0.3]) .range(["#f4c8cf", "#f8f8f8", "#c8f4cb"]); return html`${val}`; } }, "No Outliers": { formatter(val, i) { let color = d3.scaleLinear() .domain([-0.2, 0, 0.3]) .range(["#f4c8cf", "#f8f8f8", "#c8f4cb"]); return html`${val}`; } } } }); return t; }3b:T9de,Schart = { const height = 300, margin = {left:6, right:1, top: 7, bottom:5}, iwidth = width - margin.left -margin.right, iheight = height - margin.top - margin.bottom; const svg = d3.select(DOM.svg(w, h)); // define the X Axis var xAxis = d3.axisBottom() .tickFormat(d3.format(",")) .scale(xs2); var formatComma = d3.format(",") // define the Y axis var yAxis = d3.axisLeft() .scale(ys2); const g = svg.append("g") .attr("transform", `translate(${margin.left},${margin.top})`) let tooltip ; // draw the X axis g.append("g") .attr("transform", "translate(0," + (h - padding) + ")") .call(xAxis); // draw the Y axis g.append("g") .attr("transform", "translate(" + padding + ",0)") .call(yAxis); ///// labels and legends ///// // text label for the x axis g.append("text") .text(xName2) .style("text-anchor", "middle") .style("font-size", 12) .attr("font-family", "sans-serif") .attr("transform", "translate(90, 380)"); // text label for the y axis g.append("text") .text(yName2) .style("text-anchor", "left") .style("font-size", 12) .attr("font-family", "sans-serif") .attr("transform", "translate(0, 40)"); // create the circles g.selectAll("circles") .data(data) .enter() .append("circle") .attr("cx", d => xs2(d[xName2])) .attr("cy", d => ys2(d[yName2])) .attr("r", 8) .style("fill", "#243F45") .style("stroke", "white") .style("stroke-width", .6) .on("mouseover", function (d) { console.log(d); d3.select(this) .style("fill", "#3ADDD9") tooltip .attr("x", xs2(d[xName2])) .attr("y", ys2(d[yName2]) - 10) .style("display", "block") .text(function() { return `Municipio : ${d.Municipio} `+ xName2 + ' : ' + formatComma(d[xName2]) + ' '+ yName2 + ' : ' + formatComma(d[yName2]); }); }) .on("mouseout", function(d, i) { console.log(d); d3.select(this) .style("fill", "#243F45") tooltip.hide .attr("x", xs2(d[xName2])) .attr("y", ys2(d[yName2]) - 15) .style("fill", "none") }); tooltip = g.append("text") .style("font-size", "8pt") .style("font-family", "sans-serif") .style("color", "steelblue") .attr("x", -10); return svg.node(); }3c:T63e,function input(config) { let {form, type = "text", attributes = {}, action, getValue, title, description, format, submit, options} = config; if (!form) form = html``; const input = form.input; Object.keys(attributes).forEach(key => { const val = attributes[key]; if (val != null) input.setAttribute(key, val); }); if (submit) form.append(html``); form.append(html``); if (title) form.prepend(html`

${title}

`); if (description) form.append(html`

${description}

`); if (format) format = d3format.format(format); if (action) { action(form); } else { const verb = submit ? "onsubmit" : type == "button" ? "onclick" : type == "checkbox" || type == "radio" ? "onchange" : "oninput"; form[verb] = (e) => { e && e.preventDefault(); const value = getValue ? getValue(input) : input.value; if (form.output) form.output.value = format ? format(value) : value; form.value = value; if (verb !== "oninput") form.dispatchEvent(new CustomEvent("input")); }; if (verb !== "oninput") input.oninput = e => e && e.stopPropagation() && e.preventDefault(); if (verb !== "onsubmit") form.onsubmit = (e) => e && e.preventDefault(); form[verb](); } return form; }3d:Tc8b,table = (data, options) => { options = Object.assign({}, defaultOptions, options); const {sortable, rank, paged} = options; let sortKey = undefined; let sortDirection = true; let page = 0; if (sortable && rank) { throw new Error('A table can either be ranked or sortable, but not both'); } let columns = Object.keys(data[0]).map(key => { const opts = options.columns[key] || {}; return { key: key, type: opts.type || typeof data[0][key], options: opts }; }); function bake() { if (sortKey) { data = data.slice().sort((a, b) => { let as = a[sortKey]; let bs = b[sortKey]; // make this sort stable if (as == bs) return JSON.stringify(a) > JSON.stringify(b); let res = as > bs; if (sortDirection) res = !res; return res; }); } let rows = data.slice(page * paged, (page * paged) + paged); let pages = Math.ceil(data.length / paged); return html`

${options.header === false ? `` : html` ${rank ? html`` : ''} ${columns.map(c => { return th(c, sortKey, sortDirection, sortable); })} `} ${rows.map((row, i) => html` ${rank ? html`` : ''} ${columns.map(c => { let displayValue = (c.options.formatter || identity)(row[c.key], i, row); if (displayValue instanceof window.HTMLElement && displayValue.tagName == 'TD') { return displayValue; } return html`` })} `)} `; } let dom = bake(); function rerender() { dom.firstChild.remove(); dom.appendChild(bake().firstChild); } dom.addEventListener('click', e => { if (e.target.tagName === 'TH' && sortable) { if (sortKey == e.target.dataset.key) { sortDirection = !sortDirection; } sortKey = e.target.dataset.key; rerender(); } }); return dom; }3e:[] 32:{"id":"1f48898c9f148ea1","slug":"cundinamarca-colombia-2017","title":"Cundinamarca - Colombia 2017","thumbnail":"74e05eabc7ce55925793544c6e05a11ed97b759dd856169cf549767b7e106fcb","access_level":"public","create_time":"$D2018-09-11T03:24:29.498Z","update_time":"$D2018-09-24T18:37:30.132Z","view_time":null,"first_public_time":"$D2018-09-11T22:07:26.673Z","has_unpublished_edits":null,"fork":false,"stars":3,"starred":false,"owner":{"type":"team","id":"da5922f2332fd5e2","login":"monicamarcelac","name":"","avatar_url":"https://avatars-next.observableusercontent.com/ad9f2c8cad3411b8f2fb41d2e4eaf84ede302eadfc0943431cda9c659035f16f","tier":"starter_2024"},"version":1099,"publish_version":1099,"role":null,"authored":false,"authors":[{"type":"individual","id":"e85004c1fb4f77e0","login":"monicamarcelac","name":"","avatar_url":"https://avatars-next.observableusercontent.com/ad9f2c8cad3411b8f2fb41d2e4eaf84ede302eadfc0943431cda9c659035f16f","tier":null}],"members":[{"type":"individual","id":"e85004c1fb4f77e0","login":"monicamarcelac","name":"","avatar_url":"https://avatars-next.observableusercontent.com/ad9f2c8cad3411b8f2fb41d2e4eaf84ede302eadfc0943431cda9c659035f16f","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":3,"collection":{"id":"7487a8e4000b0db3","slug":"dataviz","title":"Dataviz","owner":{"id":"da5922f2332fd5e2","login":"monicamarcelac","name":""}},"type":"notebook","body":{"title":"Cundinamarca - Colombia 2017","cells":[{"id":0,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":71,"value":"md`## ¿Existe una relación entre la criminalidad y la demografía en el caso de Cundinamarca?\n

*Para visualizar de forma clara las posibles correlaciones entre las variables, se utiliza un Scatter Plot. Tenga en cuenta que las variables Código_Municipio y Municipio son categóricas!! ¡¡ No deben ser usadas en este caso!! *

\n\n

***Seleccione las variables que desea comparar***

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":169,"value":"md`#### Selecione la variable a evaluar en el eje X`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":101,"value":"viewof xName = DOM.select(Object.keys(delitos_poblacion[0]))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":175,"value":"md`#### Selecione la variable a evaluar en el eje Y\n\nFiltre preferiblemente en esta Total_Delitos`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":103,"value":"viewof yName = DOM.select(Object.keys(delitos_poblacion[0]))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":124,"value":"md`### Insight #1:\nPara la primera exploración de la información se usan los datos de la población agrupados por género, sin ver los detalles por rangos de edad. Se observa, que al comparar el total de delitos vs. las variables de población, ciertos municipios tienen valores atípicos, por lo cual, no permiten encontrar ninguna relación entre las variables. Dado esto, se hace necesario entender qué genera este efecto.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":141,"value":"md`## ¿Qué relación tienen los municipios con los delitos más reportados?`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":152,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":157,"value":"md`### Insight #2:\nLa alta participación de los delitos relacionados con estupefacientes, generan la necesidad de entender las relaciones de las variables en dos grupos separados. Esto ya que la problemática de drogas se debe ver y entender en un cotexto diferente al de los delitos comunes. Según lo anterior, se generan 2 grandes grupos: Incautación de Estupefacientes y Otros, este último agrupando todos los delitos que no tengan relación con estupefacientes`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":215,"value":"md`## ¿Cuáles delitos se agrupan como \"Otros\"?\n\n

***Entendimiento de Otros delitos: Este grupo registra en total 19 delitos, a continuación se detalla cuáles son, el número total reportado y su participación dentro del grupo***

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":597,"value":"md`#### Selecione el número de delitos que desea visualizar`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":321,"value":"viewof SelectNcrime = slider({\n min: 1, \n max: 19,\n step: 1, \n value: 6, \n description: \"Select how many crimes you want to see from 1 through 19\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":316,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":599,"value":"md`#### Participación por delito en la categoría otros`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":219,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":293,"value":"md`### Insight #4:\nAunque en este grupo se encuentran 19 tipos de delitos, solo 6 de ellos concentran aproximadamente el 70% de la participación, siendo estos los más críticos para el departamento. `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":163,"value":"md`## ¿Qué municipios tienen mayor relavancia en cada grupo?\n\n

***Filtre el grupo que desea evaluar, así como la cantidad de municipios que desea ver, para entender la cantidad de delitos que hay por municipio***

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":187,"value":"md`#### Selecione el grupo a evaluar`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":183,"value":"viewof SelectGroup = select([\"Estupefacientes\", \"Otros_Delitos\"])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":202,"value":"md`#### Selecione el número de municipios que desea observar`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":196,"value":"viewof SelectNtown = slider({\n min: 1, \n max: 116,\n step: 1, \n value: 20, \n description: \"Select how many towns you want to see from 1 through 116\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":194,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":213,"value":"md`### Insight #3:\nCon excepción de Supatá, el ranking de los municipios que tienen mayor peso en cada grupo varía, basados en esto se puede entender cuales son los municipios más golpeados por la delincuencia común y cuales, debido a su historia o cercanía con zonas productoras de estupefacientes, siguen siendo altamente afectadas por el narcotrafico. Este es el caso de Supatá que es usado como corredor de drogas para llegar a Bogotá y Guayabetal que es cercano al meta. En general, los municipios con mayor importancia dentro del grupo de Estupefacientes, tuvieron o han tenido alguna relación con grupos guerrilleros o paramilitares`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":229,"value":"md`## ¿Cómo se relacionan las variables demográficas en cada grupo?`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":232,"value":"md`Para encontrar las posibes correlaciones, se realizaron para los dos grupos 3 divisiones, las cuales son:\n\n- All Data: Se evalúa la correlación entre Total_Delitos vs. Cada grupo demográfico\n- Top 50: Se evalúa la correlación entre Total_Delitos vs. Cada grupo demográfico para los 50 municipios más relevantes\n- Sin Outliers: Se evalúa la correlación entre Total_Delitos vs. Cada grupo demográfico para el top 50 sin los múnicipios que tienen un número de delitos por encima del promedio ( top 1)\n\nEste análisis se divide en dos partes:\n\n1. Presentación de correlaciones por grupo de delitos: Esta sección le permite elegir el grupo que desea evaluar los coeficientes de correlación para cada variable demográfica vs. Total Delitos\n\n2. Presentación visual de las correlaciones (Scatter Plot) por grupos según la selección del grupo y variables`\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":269,"value":"md`### Correlaciones entre variables según grupo \n

***Seleccione el grupo a evaluar***

\n\n

*Para visualizar de forma clara las posibles correlaciones entre las variables, se utiliza un Scatter Plot. ¡¡ No debe usar las variables categóricas!! *

\n\n

*Pearson Correlation*

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":273,"value":"viewof SelectGroup3 = select([\"Correlation_Others\", \"Correlation_narcotics\"])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":286,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":235,"value":"md`### Visualización de correlaciones \n\n

***Seleccione el grupo a evaluar y sus variables, tenga en cuenta las tablas de correlaciones***

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":238,"value":"viewof SelectGroup2 = select([\"AllData_Narcotics\", \"Top50_Narcotics\",\"N.Outliers_Narcotics\",\"AllData_Otros\",\"Top50_Otros\",\"N.Outliers_Otros\"])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":244,"value":"md`##### Selecione la variable a evaluar en el eje X`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":246,"value":"viewof xName2 = DOM.select(Object.keys(data[0]))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":251,"value":"md`##### Selecione la variable a evaluar en el eje Y`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":253,"value":"viewof yName2 = DOM.select(Object.keys(data[0]))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":255,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":296,"value":"md`### Insight #5:\nLos municipios afectados por delitos comunes (grupo \"Otros\") muestran una correlación positiva con las variables demográficas, la cual se acentúa en aquellos municipios que tienen más población mayor de 60 años. Así mismo se evidencia que una mayor población de hombres podría tener un efecto positivo en el número de delitos que se presenten.\n\nSe evidencia que en los municipios con mayor número de hombres entre los 29-59 años presentan la segunda correlación más alta con delitos, por lo cual se podría asemejar este comportamiento con los encontrados en investigaciones relacionadas.\n\nContrario al comportamiento de este grupo, en estupefacientes, las correlaciones que se encontraron son negativas, lo cual justificaría que este delíto más que una relación con las variables demográficas, presentan una relación con el contexto social de la región. Valdría la pena analizar la relación de los delitos de esta región con variables de desigualdad social y económicas.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":299,"value":"md`## Conclusiones:\n\n1. Los delitos del departamento no se deben analizar como un todo, es necesario dividir los datos en al menos 2 grupos y analizar cada uno por separado.\n\n2. Los municipios afectados por Incautación de estupefacientes deben ser analizados con otras variables diferentes a las demográficas.\n\n3. Los delítos comunes si presentan una correlación positiva con las variables demográficas, lo cual implica que las conclusiones que se encuentran en algunas investigaciones del tema podrían ser aplicadas en el caso de Cundinamarca. `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":563,"value":"md`\n

***------------------------ Functions and other variables used ------------------------ ***

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":84,"value":"d3 = require(\"d3\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":88,"value":"formatter = d3.format(\".2f\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":91,"value":"padding = 60","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":93,"value":"h = 400","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":95,"value":"w = 800","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":97,"value":"ys = d3.scaleLinear()\n .domain(d3.extent(delitos_poblacion, function (d) {return d[yName];})).nice()\n .range([h - padding, padding])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":86,"value":"delitos_poblacion = d3.json(\"https://raw.githubusercontent.com/monicamarcelac/Cundinamarca/master/Delitos_Poblacion_municipio_2017.json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":99,"value":"xs = d3.scaleLinear()\n .domain(d3.extent(delitos_poblacion, function (d) {return d[xName];})).nice()\n .range([padding, w-padding])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":147,"value":"delitos_group = d3.json(\"https://raw.githubusercontent.com/monicamarcelac/Cundinamarca/master/Delitos_grupos_2017.json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":181,"value":"d3format = require(\"d3-format\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":179,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":190,"value":"dataset = d3.json(\"https://raw.githubusercontent.com/monicamarcelac/Cundinamarca/master/\"+SelectGroup+\".json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":177,"value":"function select(config = {}) {\n let {\n value: formValue,\n title,\n description,\n submit,\n multiple,\n size,\n options\n } = config;\n if (Array.isArray(config)) options = config;\n options = options.map(\n o => (typeof o === \"object\" ? o : { value: o, label: o })\n );\n const form = input({\n type: \"select\",\n title,\n description,\n submit,\n getValue: input => {\n const selected = Array.prototype.filter\n .call(input.options, i => i.selected)\n .map(i => i.value);\n return multiple ? selected : selected[0];\n },\n form: html`\n \n \n \n `\n });\n form.output.remove();\n return form;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":323,"value":"// Number of crimes in others\nd3.set(OtrosDelitos.map( d => d.Delito )).values()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":217,"value":"OtrosDelitos = d3.json(\"https://raw.githubusercontent.com/monicamarcelac/Cundinamarca/master/Otros_Delitos_2017.json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":198,"value":"function slider(config = {}) {\n let {value, min = 0, max = 1, step = \"any\", precision = 2, title, description, format, submit} = config;\n if (typeof config == \"number\") value = config;\n if (value == null) value = (max + min) / 2;\n precision = Math.pow(10, precision);\n return input({\n type: \"range\", title, description, submit, format,\n attributes: {min, max, step, value},\n getValue: input => Math.round(input.valueAsNumber * precision) / precision\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":241,"value":"data = d3.json(\"https://raw.githubusercontent.com/monicamarcelac/Cundinamarca/master/Data/\"+SelectGroup2+\".json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":276,"value":"dataCorr = d3.json(\"https://raw.githubusercontent.com/monicamarcelac/Cundinamarca/master/\"+SelectGroup3+\".json\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":278,"value":"identity = i => i","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":280,"value":"defaultOptions = ({ columns: {}, style: 'normal', paged: 25 })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":282,"value":"th = (c, sortKey, sortDirection, sortable) => {\n let {\n options: { title }\n } = c;\n let sortIndicator = sortKey && sortDirection ? \"↑\" : \"↓\";\n let arrow = html`${sortIndicator}`;\n let displayedTitle = title !== undefined ? title : c.key;\n return c.type === \"number\"\n ? html`\n ${arrow}${displayedTitle}\n `\n : html`\n ${displayedTitle}${arrow}\n `;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":284,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":259,"value":"ys2 = d3.scaleLinear()\n .domain(d3.extent(data, function (d) {return d[yName2];})).nice()\n .range([h - padding, padding])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":261,"value":"xs2 = d3.scaleLinear()\n .domain(d3.extent(data, function (d) {return d[xName2];})).nice()\n .range([padding, w-padding])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W3e","stdlib":"1","titling":"auto"}} 33:"$32:body"


${i + 1}	${displayValue}