2b:null 2c:["$","title",null,{"children":"Reordenaciones presupuestarias - Notice of Violation 2024 | José M. Zavala González | Observable"}] 31:T17f2,{ // return null let source_data; if (select_field.field === 'concepto') { source_data = comparativo_area_concepto; } else if (select_field.field === 'programa') { source_data = comparativo_area_programa; } else if (select_field.field === 'descripcion') { source_data = comparativo_area_descripcion; } // TODO: field name de cual variable usar en el graph y los margins const field_variable = select_field.field_variable let thedata = aq.from(source_data) .filter(aq.escape(d => d['area_observatorio'] === select_area)) .filter(d => Math.abs(d.variacion_dol) >= 0.1) // depends on scale y como cambiamos area pues cambia .derive({ 'tipo_cambio': d => d.variacion_dol > 0 ? 'aumento' : 'decremento', }) .orderby('variacion_dol') .objects(); // let thedata_long = aq.from(thedata) // .fold(['aumento','decremento'], {as: ['tipo_cambio', 'cantidad']}) // .objects(); const chart_width = 1000; // keep const actual_marginLeft = select_field.marginLeft; // keep const actual_marginRight = 0; const actual_tickPadding = 15; // keep. 15 is good. let barSpacing_left = 55; // changeable let barSpacing_right = 65; // changeable const inside_bar_cutoff_pixels = 60; // TODO: usando pixel-length de barra en vez del variacion dolares const variacion_extent = d3.extent(thedata, d => d.variacion_dol) const variacion_span = variacion_extent[1] - variacion_extent[0]; console.log('variacion_extent', variacion_extent) const inside_bar_cuttoff = 0; // start off at zero, pero hay que measure a bunch const gap = 40; // should stay constant. Remember, total gap width is actually 2x gap (-gap y +gap) const bar_pixels_span = chart_width - actual_marginLeft - actual_tickPadding - actual_marginRight - 2*gap - barSpacing_left - barSpacing_right; const bar_pixels_span_pos = bar_pixels_span * Math.abs(variacion_extent[1] / variacion_span); const bar_pixels_span_neg = bar_pixels_span * Math.abs(variacion_extent[0] / variacion_span); const bar_pixels_scale = d3.scaleLinear().domain([0, variacion_span]).range([0, bar_pixels_span]); const marginLeft = actual_marginLeft + gap + actual_tickPadding + barSpacing_left; const marginRight = actual_marginRight + gap + barSpacing_right; let theplot = Plot.plot({ // style: 'background-color: #eeeeee', // useful a lo que probamos margins and stuff caption: 'Fuentes: Junta de Supervisión Fiscal y análisis de Espacios Abiertos.', width: chart_width, marginLeft: marginLeft, marginRight: marginRight, // add more as needed to fit labels, random: + 30ish? color: { domain: ['aumento', 'decremento'], range: ['INDIGO', 'RED'].map(d => EA_COLORES_MAP[d]), }, x: { label: null, ticks: 0, }, y: { domain: thedata.map(d => d[field_variable]), }, marks: [ // Plot.axisX({ // tickSize: 0, // label: null, // fontSize: 12, // fontFamily: 'jaf-bernino-sans', // fontVariant: 'tabular-nums', // tickFormat: d => d === 0 ? 0 : d3.format('+$.0f')(d)+'M', // }), Plot.axisY({ tickSize: 0, label: null, fontSize: 12, fontFamily: 'jaf-bernino-sans', tickPadding: gap + actual_tickPadding + barSpacing_left, // +15 on top of gap looks nice for margin }), Plot.barX(thedata, { filter: d => d.tipo_cambio === 'aumento', x: "variacion_dol", y: field_variable, z: 'tipo_cambio', fill: 'tipo_cambio', dx: gap, }), Plot.barX(thedata, { filter: d => d.tipo_cambio === 'decremento', x: "variacion_dol", y: field_variable, z: 'tipo_cambio', fill: 'tipo_cambio', dx: -gap, }), // Labels: Monto aumento, dentro de la barra Plot.text(thedata, { filter: d => (d['tipo_cambio'] === 'aumento') & (Math.abs(bar_pixels_scale(d.variacion_dol)) >= inside_bar_cutoff_pixels), x: "variacion_dol", y: field_variable, text: d => d3.format('+$.1f')(d.variacion_dol)+'M', textAnchor: 'end', dx: gap -5, fontSize: 12, fill: 'white', fontWeight: 'bold', }), // Labels: Monto aumento, fuera de la barra Plot.text(thedata, { filter: d => (d['tipo_cambio'] === 'aumento') & (Math.abs(bar_pixels_scale(d.variacion_dol)) < inside_bar_cutoff_pixels) // & (d.variacion_dol >= 0.1) , x: "variacion_dol", y: field_variable, text: d => d3.format('+$.1f')(d.variacion_dol)+'M', textAnchor: 'start', dx: gap +5, fontSize: 12, fill: 'black', fontWeight: 'bold', }), // Labels: Monto decremento, dentro de la barra Plot.text(thedata, { filter: d => (d['tipo_cambio'] === 'decremento') & (Math.abs(bar_pixels_scale(d.variacion_dol)) >= inside_bar_cutoff_pixels), x: "variacion_dol", y: field_variable, text: d => d3.format('+$.1f')(d.variacion_dol)+'M', textAnchor: 'start', dx: -gap +5, fontSize: 12, fill: 'white', fontWeight: 'bold', }), // Labels: Monto decremento, fuera de la barra Plot.text(thedata, { filter: d => (d['tipo_cambio'] === 'decremento') & (Math.abs(bar_pixels_scale(d.variacion_dol)) < inside_bar_cutoff_pixels) // & (d.variacion_dol <= -0.1) , x: "variacion_dol", y: field_variable, text: d => d3.format('+$.1f')(d.variacion_dol)+'M', textAnchor: 'end', dx: -gap -5, fontSize: 12, fill: 'black', fontWeight: 'bold', }), // Cambio neto labels Plot.text(thedata, { x: 0, y: field_variable, text: d => d3.format('+.1%')(d.variacion_pct), // text: d => '•', fill: d => d.variacion_pct === 0 ? 'black' : d.variacion_pct > 0 ? EA_COLORES_MAP['INDIGO'] : EA_COLORES_MAP['RED'], // textAnchor: 'start', dx: gap +5, fontSize: 12, fontWeight: 'bold', }), ] }) return theplot; }32:T46b,comparativo_area_concepto = { const group_cols = ['Nombre Area Observatorio', 'Nombre Concepto'] let thedata = aq.from(sabana) .filter(d => d['Fondo'] === 'Subtotal Fondo General') .filter( d => (d['2025_version_01'] > 0) | (d['2025_version_02'] > 0) ) .groupby(group_cols) .rollup({ '2025_version_01': op.sum('2025_version_01'), '2025_version_02': op.sum('2025_version_02'), }) .derive({ 'Variacion': d => (d['2025_version_02'] - d['2025_version_01']), }) .derive({ 'Variacion %': aq.escape(d => (d['2025_version_01'] !== 0n) ? ( Number(d['Variacion']) / Number(d['2025_version_01']) ) : null), }) .orderby(group_cols) .rename({ 'Nombre Area Observatorio': 'area_observatorio', 'Nombre Concepto': 'nombre_concepto', 'Variacion': 'variacion_dol', 'Variacion %': 'variacion_pct', }) .objects() const cols_scale = ['variacion_dol', '2025_version_01', '2025_version_02']; thedata.forEach(d => { for (let c of cols_scale) { d[c] = Number(d[c]) / 1e3 // miles a millones } }) return thedata }33:T46b,comparativo_area_programa = { const group_cols = ['Nombre Area Observatorio', 'Nombre Programa'] let thedata = aq.from(sabana) .filter(d => d['Fondo'] === 'Subtotal Fondo General') .filter( d => (d['2025_version_01'] > 0) | (d['2025_version_02'] > 0) ) .groupby(group_cols) .rollup({ '2025_version_01': op.sum('2025_version_01'), '2025_version_02': op.sum('2025_version_02'), }) .derive({ 'Variacion': d => (d['2025_version_02'] - d['2025_version_01']), }) .derive({ 'Variacion %': aq.escape(d => (d['2025_version_01'] !== 0n) ? ( Number(d['Variacion']) / Number(d['2025_version_01']) ) : null), }) .orderby(group_cols) .rename({ 'Nombre Area Observatorio': 'area_observatorio', 'Nombre Programa': 'nombre_programa', 'Variacion': 'variacion_dol', 'Variacion %': 'variacion_pct', }) .objects() const cols_scale = ['variacion_dol', '2025_version_01', '2025_version_02']; thedata.forEach(d => { for (let c of cols_scale) { d[c] = Number(d[c]) / 1e3 // miles a millones } }) return thedata }34:T462,comparativo_area_descripcion = { const group_cols = ['Nombre Area Observatorio', 'DESCRIPCION'] let thedata = aq.from(sabana) .filter(d => d['Fondo'] === 'Subtotal Fondo General') .filter( d => (d['2025_version_01'] > 0) | (d['2025_version_02'] > 0) ) .groupby(group_cols) .rollup({ '2025_version_01': op.sum('2025_version_01'), '2025_version_02': op.sum('2025_version_02'), }) .derive({ 'Variacion': d => (d['2025_version_02'] - d['2025_version_01']), }) .derive({ 'Variacion %': aq.escape(d => (d['2025_version_01'] !== 0n) ? ( Number(d['Variacion']) / Number(d['2025_version_01']) ) : null), }) .orderby(group_cols) .rename({ 'Nombre Area Observatorio': 'area_observatorio', 'DESCRIPCION': 'descripcion', 'Variacion': 'variacion_dol', 'Variacion %': 'variacion_pct', }) .objects() const cols_scale = ['variacion_dol', '2025_version_01', '2025_version_02']; thedata.forEach(d => { for (let c of cols_scale) { d[c] = Number(d[c]) / 1e3 // miles a millones } }) return thedata }35:[{"id":"f47721805312c1b8d5c46e576834aadc055d777cffec8820c9f2f3d1f9753766279cf32f9d3a41f74e27be633e3bb5bce43c7d7d051d8d46f43bcead6d1aa3f1","href":"https://static.observableusercontent.com/files/f47721805312c1b8d5c46e576834aadc055d777cffec8820c9f2f3d1f9753766279cf32f9d3a41f74e27be633e3bb5bce43c7d7d051d8d46f43bcead6d1aa3f1","name":"sabana_with_area.parquet","type":"application/octet-stream","lastModified":1718130837729.476,"size":987565},{"id":"d605b0b625db65039982200c1e1bee069e08fa9463cce0448647dcca53864492a65028bb7b3c1d4d9e3ed391bec1ff25758a0086af08fdc4e9f3a210bf82611f","href":"https://static.observableusercontent.com/files/d605b0b625db65039982200c1e1bee069e08fa9463cce0448647dcca53864492a65028bb7b3c1d4d9e3ed391bec1ff25758a0086af08fdc4e9f3a210bf82611f","name":"fondo_general_area_observatorio_agencia.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1718130837729.476,"size":11314},{"id":"b71c9ed71f3ce9006ad10f4d288865509a0357f5999d5efef984a5e94535b9950c70632f0f694b19fa3475782b8cde8ab15862ab7f2966d9270ffda6d013b373","href":"https://static.observableusercontent.com/files/b71c9ed71f3ce9006ad10f4d288865509a0357f5999d5efef984a5e94535b9950c70632f0f694b19fa3475782b8cde8ab15862ab7f2966d9270ffda6d013b373","name":"fondo_general_concepto_descripcion.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1718130837729.476,"size":17201},{"id":"53588068d39a8542ab7b1fccf8af6a6bf00167813ecae763397dfdef3c51d237e675be1d6518e3ec68e87123b308687e82e90913e0662c12b76885e730d0d2e5","href":"https://static.observableusercontent.com/files/53588068d39a8542ab7b1fccf8af6a6bf00167813ecae763397dfdef3c51d237e675be1d6518e3ec68e87123b308687e82e90913e0662c12b76885e730d0d2e5","name":"Analysis_FOMB_NoV_05212024@5.xlsx","type":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","lastModified":1718130837729.476,"size":28579}] 2f:{"id":"08edcbef064095d3","slug":null,"title":"Reordenaciones presupuestarias - Notice of Violation 2024","thumbnail":"cb6ec9b810b769c64502bac1d83e32b5fcb686a48106c7d2a07ddd2220e86b6b","access_level":"public","create_time":"$D2024-06-11T18:33:57.729Z","update_time":"$D2024-06-11T19:59:51.539Z","view_time":null,"first_public_time":"$D2024-06-11T18:33:57.729Z","fork":{"id":"ade58ee2d1fda4dc","slug":null,"title":"FOMB PR: Notice 2024","owner":{"id":"247b19faa48b7d89","login":"jzavala-gonzalez","name":"José M. 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","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":344,"value":"# Apéndice","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":906,"value":"selectable_fields = [\n {field_label: 'Concepto', field: 'concepto', listado_area: listado_areas_1, field_variable: 'nombre_concepto', marginLeft: 260},\n {field_label: 'Programa', field: 'programa', listado_area: listado_areas_2, field_variable: 'nombre_programa', marginLeft: 260},\n {field_label: 'Descripción', field: 'descripcion', listado_area: listado_areas_3, field_variable: 'descripcion', marginLeft: 350},\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":670,"value":"listado_areas_1 = Array.from(new Set(comparativo_area_concepto\n.filter(d => (d.Variacion !== 0) & (Math.abs(d.variacion_dol) >= 0.1))\n.map(d => d['area_observatorio'])))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":680,"value":"listado_areas_2 = Array.from(new Set(comparativo_area_programa\n.filter(d => (d.Variacion !== 0) & (Math.abs(d.variacion_dol) >= 0.1))\n.map(d => d['area_observatorio'])))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":862,"value":"listado_areas_3 = Array.from(new Set(comparativo_area_descripcion\n.filter(d => (d.Variacion !== 0) & (Math.abs(d.variacion_dol) >= 0.1))\n.map(d => d['area_observatorio'])))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":509,"value":"estilos_2 = 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'ninguno'\n }\n }\n })\n .groupby('area_observatorio', 'tipo_cambio')\n .rollup({\n 'cantidad': op.sum('cantidad')\n })\n .groupby('area_observatorio')\n .pivot('tipo_cambio', 'cantidad')\n .impute({ aumento: () => 0, decremento: () => 0 })\n .derive({\n 'cambio_neto': d => d.aumento + d.decremento,\n })\n .orderby('cambio_neto')\n .objects()\n\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":375,"value":"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":357,"value":"Math.sign(0)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":605,"value":"import {DuckDBClientKL} from \"@kimmolinna/duckdbclient\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":594,"value":"// db = DuckDBClientKL.of({\ndb = DuckDBClient.of({\n sabana: FileAttachment(\"sabana_with_area.parquet\")\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":538,"value":"comparativo_area = aq.from(comparativo_area_agencia)\n.groupby('area_observatorio')\n .rollup({\n '2025_version_01': op.sum('2025_version_01'),\n '2025_version_02': op.sum('2025_version_02'),\n 'variacion_dol': op.sum('variacion_dol'),\n })\n .derive({\n 'variacion_pct': d => d.variacion_dol / d['2025_version_01']\n })\n .orderby('variacion_dol')\n.objects()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":529,"value":"comparativo_area_agencia = {\n let workbook = await FileAttachment('fondo_general_area_observatorio_agencia.xlsx').xlsx()\n let data = workbook.sheet('Sheet1', {headers: true})\n data = aq.from(data)\n .rename({\n 'Nombre Area Observatorio': 'area_observatorio',\n 'Nombre Agencia': 'nombre',\n 'Variacion': 'variacion_dol',\n 'Variacion %': 'variacion_pct',\n })\n .derive({\n '2025_version_01': d => d['2025_version_01'] / 1e3,\n '2025_version_02': d => d['2025_version_02'] / 1e3,\n 'variacion_dol': d => d.variacion_dol / 1e3, // cambiar de miles a millones\n })\n .objects();\n return data\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":567,"value":"comparativo_concepto = aq.from(comparativo_concepto_descripcion)\n.groupby('nombre_concepto')\n .rollup({\n '2025_version_01': op.sum('2025_version_01'),\n '2025_version_02': op.sum('2025_version_02'),\n 'variacion_dol': op.sum('variacion_dol'),\n })\n .derive({\n 'variacion_pct': d => d.variacion_dol / d['2025_version_01']\n })\n .orderby('variacion_dol')\n.objects()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":564,"value":"comparativo_concepto_descripcion = {\n let workbook = await FileAttachment('fondo_general_concepto_descripcion.xlsx').xlsx()\n let data = workbook.sheet('Sheet1', {headers: true})\n data = aq.from(data)\n .rename({\n 'Nombre Concepto': 'nombre_concepto',\n 'DESCRIPCION': 'descripcion',\n 'Variacion': 'variacion_dol',\n 'Variacion %': 'variacion_pct',\n })\n .derive({\n '2025_version_01': d => d['2025_version_01'] / 1e3,\n '2025_version_02': d => d['2025_version_02'] / 1e3,\n 'variacion_dol': d => d.variacion_dol / 1e3, // cambiar de miles a millones\n })\n .objects();\n return data\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":109,"value":"workbook = FileAttachment(\"Analysis_FOMB_NoV_05212024@5.xlsx\").xlsx()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":110,"value":"workbook.sheetNames","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"denied_items = {\n let data = workbook.sheet('denied', {\n headers: true,\n // range: \"A1:J10\"\n })\n\n data.forEach(d => {\n d.status = 'denied';\n d.label = d.nombre\n if (d.bajo_custodia) {\n d.label += '*'\n }\n })\n return data\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":190,"value":"partially_approved_items = {\n let data = workbook.sheet('partially_approved', {\n headers: true,\n // range: \"A1:J10\"\n })\n\n data.forEach(d => {\n d.status = 'partially_approved';\n d.label = d.nombre\n if (d.bajo_custodia) {\n d.label += '*'\n }\n })\n return data\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":309,"value":"approved_items = {\n let data = workbook.sheet('approved', {\n headers: true,\n // range: \"A1:J10\"\n })\n\n data.forEach(d => {\n d.status = 'approved';\n d.label = d.nombre\n if (d.bajo_custodia) {\n d.label += '*'\n }\n })\n return data\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":277,"value":"readjusted_items = {\n let data = workbook.sheet('reajustes', {\n headers: true,\n // range: \"A1:J10\"\n })\n\n data.forEach(d => {\n d.status = 'readjusted';\n d.label = d.nombre\n if (d.bajo_custodia) {\n d.label += '*'\n }\n })\n return data\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":338,"value":"all_items = [\n ...denied_items,\n ...partially_approved_items,\n ...approved_items,\n ...readjusted_items,\n]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"fmt = n => d3.format(\",d\")(n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"plotLabel = (data, dy) => \n Plot.text(data, {\n x: \"partida\",\n y: \"accu\",\n dy: dy, \n //frameAnchor: anchor,\n fontWeight: \"bold\",\n text: d => d3.format(\"$,.1f\")(d.accu)+'M',\n fontSize: 16, // stroke: 'none', fill: 'white',\n fontVariant: 'tabular-nums',\n fontFamily: 'jaf-bernino-sans',\n })","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"waterfall = function f(numbers,accu_start, name) {\n let last = 0, accu = accu_start; \n let waterfall = numbers.map((d, i) => {\n last = accu;\n accu += d.profit;\n return {\n [name]: d[name],\n nextDay: i < (numbers.length - 1) ? numbers[i + 1][name] : \"Total\",\n prior: last,\n accu: accu,\n profit: d.profit\n };\n });\n\n waterfall = [\n {\n [name]: \"Inicial\",\n nextDay: numbers[0][name],\n prior: accu_start,\n accu: accu_start,\n profit: 0\n },\n ...waterfall,\n {\n [name]: \"Total\",\n nextDay: null,\n prior: accu_start,\n accu: accu,\n profit: 0\n }\n ]\n \n // waterfall.push({\n // partida: \"Total\",\n // nextDay: null,\n // prior: accu_start,\n // accu: accu,\n // profit: 0\n // });\n \n return waterfall;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":74,"value":"waterfall(\n fomb_adjustment.filter(d => (d.partida !== 'Partial') | show_partial)\n .map(d => Object({...d, profit: d.cantidad})), 13062.30 ,'partida')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7,"value":"fomb_adjustment = [\n {partida: 'En cumplimiento', cantidad: 130.70},\n {partida: 'Revisado con aumento', cantidad: 291.09},\n {partida: 'Revisado con decremento', cantidad: -20.72},\n {partida: 'Denegado', cantidad: -396.96},\n {partida: 'Parcialmente aprobado', cantidad: -118.90, partial: true},\n]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"fonts_link = \"https://use.typekit.net/szl4srx.css\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"value":"fonts_link_element = \n// Importante para ver los fonts en el editor de Observable (o sea aqui)\nhtl.html`\n\n`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":38,"value":"estilos = htl.html`\n\n`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":138,"value":"import { EA_COLORES_MAP} from \"22dc6182207c44c8\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":352,"value":"import {aq, op} from '@uwdata/arquero';","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W35","stdlib":"1","titling":"auto"}} 30:"$2f:body"