2b:null 2c:["$","title",null,{"children":"Table format experimentos | José M. Zavala González | Observable"}] 31:T6ac,Plot.plot({ height: 260, width: 300, marginLeft: 90, marginRight: 60, marks: [ Plot.axisY({ fontSize: 12, fontWeight: 'bold', label: null, tickSize: 0, // tickPadding: 1 fontFamily: 'B612 Mono', }), Plot.axisX({ ticks: 0, fontWeight: 'bold', // fontVariant: 'tabular-nums', fontFamily: 'B612 Mono', tickSize: 0, label: null, fontSize: 12, // tickFormat: ',.0s', }), Plot.barX(sample_data, {x: 1, y: "region", fill: '#eeeeee', // inset: 10, insetTop: 5, insetBottom: 5, // inset: 0, // sort: {y: "x", reverse: true} }), Plot.barX(sample_data, {x: d => median_ratio_scaler(d.median_ratio), y: "region", // inset: 10, insetTop: 5, insetBottom: 5, // inset: 0, // sort: {y: "x", reverse: true} }), Plot.text(sample_data, {x: d => 2, y: "region", // inset: 10, text: 'clientes', textAnchor: 'end', fontSize: 12, fontFamily: 'B612 Mono', fontWeight: 'bold', dx: 5, // inset: 0, // sort: {y: "x", reverse: true} }), // Plot.ruleX([0]) ] })32:T5b7,{ const dataWidth = width; const marginLeft = 50; const marginRight = 50; const m4_regions_service_total = m4(regions_service_total, dataWidth, 'timestamp', 'totalClientsWithoutService') const service_threshold = 10000 return Plot.plot({ width: dataWidth + marginLeft + marginRight, marginLeft, marginRight, y: { grid: false, // domain: [0,50000], }, marks: [ Plot.gridY({stroke: "black", strokeOpacity: 0.2}), Plot.line( m4_regions_service_total, { x: 'timestamp', y: 'totalClientsWithoutService', // stroke: 'steelblue', tip: true, // strokeWidth: .8, }), Plot.areaY( m4_regions_service_total, { x: 'timestamp', y1: d => d['totalClientsWithoutService'] >= service_threshold ? 0 : null, y2: d => d['totalClientsWithoutService'] >= service_threshold ? d['totalClientsWithoutService'] : null, // stroke: 'steelblue', fill: 'red', fillOpacity: 0.5, //stroke: 'red', strokeOpacity: 1, tip: false, // strokeWidth: .8, }), Plot.line( m4_regions_service_total, { x: 'timestamp', y: d => d['totalClientsWithoutService'] >= service_threshold ? d['totalClientsWithoutService'] : null, // stroke: 'steelblue', // fill: 'red', fillOpacity: 0.5, stroke: 'red', strokeOpacity: 1, tip: false, // strokeWidth: .8, }), Plot.ruleY([0]), ] }) }33:[] 2f:{"id":"64335017017e946f","slug":null,"title":"Table format experimentos","thumbnail":"698b7987ddd93e6439748c603326a1d755c2b604af66c4136e6ce1b267af0f65","access_level":"public","create_time":"$D2023-12-09T01:57:38.479Z","update_time":"$D2023-12-16T02:08:43.238Z","view_time":null,"first_public_time":"$D2023-12-09T01:57:38.479Z","fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"247b19faa48b7d89","login":"jzavala-gonzalez","name":"José M. Zavala González","avatar_url":"https://avatars-next.observableusercontent.com/c80357963553ac341ea90ed3d79296a72d004aa90d9b89afd76f17e04dcf9277","tier":"starter_2024"},"version":348,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"2c62f0243f8f45b0","login":"jzavala-gonzalez","name":"José M. Zavala González","avatar_url":"https://avatars-next.observableusercontent.com/c80357963553ac341ea90ed3d79296a72d004aa90d9b89afd76f17e04dcf9277","tier":null}],"members":[{"type":"individual","id":"2c62f0243f8f45b0","login":"jzavala-gonzalez","name":"José M. Zavala González","avatar_url":"https://avatars-next.observableusercontent.com/c80357963553ac341ea90ed3d79296a72d004aa90d9b89afd76f17e04dcf9277","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Table format experimentos","cells":[{"id":0,"value":"# Table format experimentos","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":84,"value":"En monospace span:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":6,"value":"\n Resumen del 8 de diciembre de 2023

\n Región------Clientes---------Hora

\n Arecibo........2,689......7:05 AM
\n Bayamón........1,498......4:00 AM
\n Caguas.........2,200......4:30 PM
\n Carolina.......2,055.....11:05 PM
\n Mayagüez.......7,121.....11:25 AM
\n Ponce..........2,775......2:50 PM
\n San Juan......16,506......2:45 PM
\n ____________________
\n Total.........34,844
\n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":112,"value":"Me gusta el simplicity but I get no sense of scale unless I start actually reading and that's too much cognitive load for me rn.\n\nLight graphic:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":115,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":117,"value":"sample_data = {\n let thedata = [\n {region: 'Arecibo', clientes: 2689},\n {region: 'Bayamón', clientes: 1498},\n {region: 'Caguas', clientes: 2200},\n {region: 'Carolina', clientes: 2055},\n {region: 'Mayagüez', clientes: 7121},\n {region: 'Ponce', clientes: 2775},\n {region: 'San Juan', clientes: 16506},\n]\n\n thedata.forEach(d => {\n let themedian = 5000\n if (d.region === 'Carolina') {themedian = 4200}\n d.median_ratio = d.clientes / themedian\n })\n\n return thedata\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":171,"value":"Y normalmente San Juan sesgaria las barras pero estamos normalizando por la mediana y usando un log scale. Es arbitrario a proposito porque solo buscamos proveer un efecto cualitativo para guiar el ojo hacia los numeros \"más grandes\" relativamente.\n\nNota: La mediana por region es alrededor de 5,000 clientes afectados al dia, excepto para Carolina que es cerca de 4,200.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":207,"value":"Plot.plot({\n marginLeft: 100,\n // x: {type: 'log'},\n marks: [\n Plot.axisY({\n tickSize: 0,\n }),\n \n Plot.boxX(regional_dailies, {x: \"clientes_afectados\", y: \"region_name\",\n // sort: {y: \"x\"}\n }),\n Plot.ruleX([5000], {stroke: 'red'}), // eyeballing la mediana\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":323,"value":"median_ratio_scaler(3.3012)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":328,"value":"d3.extent(regional_dailies, d => d.median_ratio)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":340,"value":"median_ratio_scaler.domain()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":296,"value":"median_ratio_scaler = \nd3.scaleLog([0, 1])\n// .domain(d3.extent(regional_dailies, d => d.median_ratio))\n.domain([0.0625, d3.max(regional_dailies, d => d.median_ratio)])\n.base(2) // TODO: Add clamp left al range para que no se vaya negativo","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":257,"value":"Plot.plot({\n height: 500,\n marginRight: 100,\n x: {\n 'type': 'log',\n base: 2,\n domain: d3.extent(regional_dailies, d => d.median_ratio),\n },\n marks: [\n // Plot.axisX({type: 'log'}),\n Plot.rectY(regional_dailies, Plot.binX({y: \"count\"}, {x: \"median_ratio\", fy: 'region_name', tip:true})),\n Plot.ruleY([0])\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":233,"value":"Parece que las regiones tienen medianas similares??","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":235,"value":"select region_name,\n median(clientes_afectados) as day_median,\n mean(clientes_afectados) as day_mean,\nfrom regional_dailies\ngroup by region_name","pinned":true,"hidden":false,"mode":"sql","author":"$undefined","summary":"$undefined","output":"","database":"var:regional_dailies"},{"id":195,"value":"with initial_table as (\nselect\n strftime(\"timestamp\", '%Y-%m-%d')::DATE as timestamp_date,\n region_name,\n max(totalClientsWithoutService) as clientes_afectados,\nfrom regionsWithoutService\n where \"type\" = 'region'\ngroup by timestamp_date, region_name\n)\n\nselect *,\n median(clientes_afectados) over (partition by (region_name)) as day_median,\n clientes_afectados / day_median as median_ratio\nfrom initial_table\norder by timestamp_date, region_name\n","pinned":true,"hidden":false,"mode":"sql","author":"$undefined","summary":"$undefined","output":"regional_dailies","database":"var:datadb"},{"id":178,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":190,"value":"select *\nfrom regionsWithoutService","pinned":true,"hidden":false,"mode":"sql","author":"$undefined","summary":"$undefined","output":"regions_without_service","database":"var:datadb"},{"id":110,"value":"# Apendice","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":4,"value":"","pinned":true,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":181,"value":"import {m4} from \"@uwdata/m4-scalable-time-series-visualization\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":184,"value":"import {datadb} from \"3bd1064313a4d2c3\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 30:"$2f:body"