25:["$","title",null,{"children":"Retroingénérie de l'utilisation du Webservice avec D3 | Benjamin Picod | Observable"}] 49:T650,chart = { let idbanks = ["010536463", "010536465"] const url = "https://bdm.insee.fr/series/sdmx/data/SERIES_BDM/" + idbanks.join("%2B") // "%2B" équivaut à "+" let xml_string = await fetch(url).then( response => response.text() ) let xml_doc = (new DOMParser).parseFromString(xml_string, "application/xml") let xml_nodelist = d3.hierarchy(xml_doc).descendants() let dt = xml_nodelist .filter(d => d.data.tagName == "Obs") .map(d => { return {TIME_PERIOD: d.data.getAttribute("TIME_PERIOD"), OBS_VALUE: +d.data.getAttribute("OBS_VALUE"), TITLE: d.parent.data.getAttribute("TITLE_FR")} }) return vl.markLine({interpolate:'cardinal'}) .encode( vl.x().fieldT('TIME_PERIOD').title(null), vl.y().fieldQ('OBS_VALUE').title(null).scale({zero: false}), vl.color().fieldN('TITLE').legend({orient:'top', symbolStrokeWidth: 3, symbolSize: 400, labelFontSize: 11, title: null, labelLimit: 300}), vl.tooltip([vl.tooltip().fieldT('TIME_PERIOD').title('période ').format('%Y'), vl.tooltip().fieldQ('OBS_VALUE').format(',').title('valeur ')]) ) .data(dt) .title({anchor:'middle', text: "Mon 1er graphique connecté au Web Service BDM", subtitle: 'Source : Insee BDM' }) .width("container") .height(250) .render({renderer: 'svg'}) }4a:T5d8,dtfTb = { const url = "https://bdm.insee.fr/series/sdmx/dataflow/FR1/all" let xml_string = await fetch(url).then( response => response.text() ) let xml_doc = (new DOMParser).parseFromString(xml_string, "application/xml") // XMLDocument let xml_nodelist = d3.hierarchy(xml_doc).descendants() let urls = xml_nodelist.filter(d => d.data.tagName == "com:AnnotationURL") .map(d => ({ url : d.data.innerHTML, dataset : d.parent.parent.parent.data.getAttribute('id') }) ) let libs = xml_nodelist.filter(d => d.data.tagName == "com:Name" && d.data.getAttribute('xml:lang') == 'fr' ) .map(d => ({ lib : d.data.innerHTML, dataset : d.parent.data.getAttribute('id') }) ) let series = xml_nodelist.filter(d => d.data.tagName == "com:AnnotationText") .map(d => ({ series : +d.data.innerHTML.split(':')[1], dataset : d.parent.parent.parent.data.getAttribute('id') }) ) let structures = xml_nodelist.filter(d => d.data.tagName == "str:Structure") .map(d => ({ structure : d.children[0].data.getAttribute('id'), dataset : d.parent.data.getAttribute('id') }) ) return aq.from(urls).join(aq.from(libs)) .join(aq.from(series)) .join(aq.from(structures)) // jointure auto sur le champ commun id }4b:T750,getCodelist = async function(cl) { if (!cl) return false if (codelistMap.has(cl)) return codelistMap.get(cl) if (codelistMap.get(cl) === "fetching") // récup en cours, pas la peine de déclencher un nouveau chargement return codelistMap.set(cl, "fetching") const url = "https://bdm.insee.fr/series/sdmx/codelist/FR1/" + cl // gestion du quota de 30 requêtes max par minute pour une clé // s'il est dépassé, on passe à une autre clé via get_fetch_options() let i = 0, xml_codelist_bdm while (i++ <= 5) { // 5 tentatives max xml_codelist_bdm = await fetch(url) .then( response => { if (response.status == 429) { return {error: 429, msg: response.text() } } //quota dépassé return response.text() }) if (typeof xml_codelist_bdm == 'string') i = 10 } let xml_tree = (new DOMParser).parseFromString(xml_codelist_bdm, "application/xml") let nodes = d3.hierarchy(xml_tree) let a = nodes.descendants().filter(d => d.data.tagName == "str:Code") .map(d => { return {id:d.data.getAttribute("id"), lib: d.children.filter(e => e.data.tagName == "com:Name" && e.data.getAttribute('xml:lang') == 'fr')[0].data.innerHTML, c: d.parent.data.getAttribute("id") }}) let b = nodes.descendants().filter(d => d.data.tagName == "str:Codelist") .map(d => d.children.filter(e => e.data.tagName == "com:Name" && e.data.getAttribute('xml:lang') == 'fr')[0].data.innerHTML) codelistLibMap.set(cl, b[0]) let dt = aq.from(a) codelistMap.set(cl, aq.from(a)) // stockage dans une hashmap centrale sous forme d'une table Arquero return dt }4c:T48d,import {fetchp_txtfile_from_zip} from '@ericmauviere/arquero-table-utils' /*jszip = require("jszip@3.6.0/dist/jszip.min.js") import { fetchp } from "@tomlarkworthy/fetchp" fetchp_txtfile_from_zip = async function(zipurl, csvname, options = { proxy: false } ) { if (!options.max_age) options.max_age = 24 * 7 * 3600 let results = await fetchp(zipurl, { headers: { 'x-requested-with': "observablehq.com" // Upstream blocks us without this, silly }, responseHeaders: { 'transfer-encoding': null, // Its trying to send them in a chunked reponse which is not working ATM 'Cache-control': `public, max-age=${options.max_age}` // We can cache at the proxy level now too! } }); if (results.status !== 200) throw new Error(`Error status: ${results.status} ${await results.text()}`) return await jszip.loadAsync(results.arrayBuffer()) .then(buf => { if (options.listfiles) console.log(Object.keys(buf.files)) if (csvname && !buf.files.hasOwnProperty(csvname)) return false if (!buf.files.hasOwnProperty(csvname)) csvname = Object.keys(buf.files)[0] return buf.file(csvname).async("string") }) }*/4d:T1359,idbanksList = { cls0 return [ {lib: 'TRAVAIL - Taux de chômage au sens du BIT', idbanks: ["001688527"]}, {lib: 'TRAVAIL - Taux de chômage au sens du BIT - par sexe', idbanks: ['001688533','001688535'], sort:1}, {lib: 'TRAVAIL - Taux de chômage au sens du BIT - par âge', idbanks: ['001688529','001688531','001688537']}, {lib: "TRAVAIL - Demandeurs d'emploi cat. A", idbanks: ['010596995','010597225']}, {lib: 'TRAVAIL - Personnes dans le halo autour du chômage - par âge', idbanks: ['010607885','010607886','010607887']}, {lib: "DEV DURABLE - Part des individus s'étant connectés à internet les 3 derniers mois", idbanks: [ '010594690','010594691','010594692','010594693','010594694']}, {lib: "DEMOGRAPHIE - Taux de fécondité", idbanks: ['001686827','001686828','001686829','001686830','001686831']}, {lib: 'TRAVAIL - Emploi', idbanks: ["010550772", '010550769', '010550785', '010550801', '010550782']}, {lib: "SOCIAL - Evolution du pouvoir d'achat arbitrable par UC", idbanks: ["010562210"], y0:0}, {lib: "ECO - Nombre de créations d'entreprises", idbanks: ["001564318"]}, {lib: "ECO - Nombre de créations d'entreprises - micro-entrepreneurs transports", idbanks: ["001786622"]}, {lib: "DEMOGRAPHIE - Taux de mortalité infantile", idbanks: ["000067681"]}, {lib: "DEMOGRAPHIE - Espérance de vie à la naissance ", idbanks: ["001686946", "001686951"], zoom:1}, {lib: "ECO - Nombre de défaillances d'entreprises", idbanks: ["001656101"]}, {lib: "ECO - Dette négociable de l'État", idbanks: ["001738855"]}, {lib: "SOCIAL - Indicateur synthétique de confiance des ménages ", idbanks: ["001587668"], y0:100, zoom: 1}, {lib: "ECO - Indicateur synthétique du climat des affaires dans les services", idbanks: ["001587025"], y0:100, zoom:1}, {lib: "SOCIAL - Variation annuelle des loyers", idbanks: ["010600393", "010600400"], y0:0}, {lib: "ECO - Indice mensuel des prix agricoles à la production", idbanks: ["010538726", "010538633", "010538718"], y0:100, zoom:1}, {lib: "PRIX - Téléphones portables", idbanks: ["001764900"], y0:100}, {lib: "PRIX - Cigarettes", idbanks: ["001764555"], y0:100}, {lib: "DEMOGRAPHIE - Âge moyen des mères à l'accouchement", idbanks: ["001686826"], zoom:1}, {lib: "PRIX - Légumes ", idbanks: ["001764470", "001764472", "001764474"], y0:100}, {lib: "PRIX - Fruits ", idbanks: ["001764461", "001764463", "001764465"], y0:100}, {lib: "PRIX - Poissons ", idbanks: ["001764418", "001764420"], y0:100}, {lib: "PRIX - Divers ", idbanks: ["001764486", "001764513", "001764481"], y0:100, sort:1}, {lib: "PRIX - Indice des prix dans la grande distribution ", idbanks: ["001768741", "001768742", "001768743", "001768736"], y0:100, sort: 1}, {lib: "PRIX - Indice des prix grande distribution et autres ", idbanks: ["001768737", "001768739"], y0:100}, {lib: "ECO - Pétrole brut Brent (Londres) – Indice en euros", idbanks: ["010002091"], y0:100, zoom:1}, {lib: "ECO - Indices de prix et cours des matières premières", idbanks: ["010002095","010002098"], y0:100, zoom:1}, {lib: "SOCIAL - Indice de référence des loyers (IRL)", idbanks: ["001515334"], y0:0, zoom:1}, {lib: "DEMOGRAPHIE - Nombre total de mariages enregistrés", idbanks: ["001641595"]}, {lib: "DEMOGRAPHIE - Nombre de Pactes civils de solidarité (Pacs)", idbanks: ["001686967"]}, {lib: "DEMOGRAPHIE - Taux de natalité - par département", idbanks: ["001747930", "001747956","001747895", "001747970", "001747969"], sort:1}, {lib: "DEV DURABLE - Agriculture biologique", idbanks: ["010594425"]}, {lib: "DEV DURABLE - Prévalence du tabagisme quotidien par niveau de diplôme", idbanks: ["010593319","010593321", "010593318"], sort:1}, {lib: "DEV DURABLE - Taux standardisés de décès pour cause de suicide", idbanks: ["010593279","010593280"], sort:1}, {lib: "DEV DURABLE - Nombre de tués par accident de la route", idbanks: ['010593289','010593290','010593291','010593292','010593293','010593294','010593295'], sort:1}, {lib: "DEV DURABLE - Part des énergies renouvelables (EnR)", idbanks: ["010596107"]}, {lib: "SOCIAL - Résidences principales - Proportion de logés gratuitement", idbanks: ["001687227"]}, {lib: "DEMOGRAPHIE - Excédents naturel et migratoire", idbanks: ["001641585", "001641597"]}, {lib: "TRAVAIL - Montants mensuels du SMIC", idbanks: ["000879877", "000879878"]}, {lib: "TRAVAIL - Taux de chômage localisé par département", idbanks: ["001515957", "001515933", "001515940", "001515918"], sort:1}, {lib: "TRAVAIL - Emploi total au 31 décembre", idbanks: ["001666189", "001666540", "001665528", "001665881","001666233"], sort:1}, {lib: "ECO - Nombre d’hôtels", idbanks: ["010609555", "010609556", "010609557"], sort:1}, ].sort((a,b) => b.lib < a.lib ? 1 : -1) }4e:T685,data_id_bank = { let idbank = selectedIdbank if (!idbank) return {} const url = "https://bdm.insee.fr/series/sdmx/data/SERIES_BDM/" + (Array.isArray(idbank) ? idbank.join('%2B') : idbank) // 1 - métadonnées relatives aux idbanks passés en entrée let dt = idbanksDt.params({idbank}) .derive({idbank: d => op.padstart(d.idbank, 9, '0')}) .filter(d => op.includes(idbank, d.idbank)) let dst_def = await getDstDef(dt.get('famille')) // 2 - accès aux dimensions du dataset contenant ces idbanks let dims = dst_def.dimensions, // safe list_var = dt.get('list_var').split('.') // unsafe, fichiers csv idbanks dims = dims.slice(0, list_var.length) // dims a pu s'étendre... let dt2 = dt.derive({spread: d => op.split(d.list_mod, '.')}) .spread('spread', { as: dims }) // 3 - recherche de la dimension selon laquelle on a sélectionné des idbanks multiples (ex : tranches d'âge) let spread_dimension = Array.isArray(idbank) && idbank.length > 1 ? dims.filter(d => dt2.params({d}).dedupe(d).numRows() > 1)[0] : null // 4 - chargement de la nomenclature (codelist) associée à cette dimension if (spread_dimension) await getCodelist(dst_def.indic_to_codelist.get(spread_dimension)) let idbank_map = spread_dimension ? dt2.params({spread_dimension}) .rollup({map: op.map_agg('idbank', spread_dimension)}).get('map') : null return {tb: await getBdmData(url, false, spread_dimension, idbank_map), spread_dimension, idbank_map, dst_def} }4f:Taa6,getBdmData = async function(url_sdmx, multi_geo, spread_dimension, idbank_map) { // 1 - acquisition des données, gestion des erreurs potentielles ou du quota de 30 requêtes par minute let i = 0, xml_data_bdm while (i++ <= 5) { xml_data_bdm = await fetch(url_sdmx) .then( response => { if (response.status == 429) { return {error: response.status, msg: response.text() } } return response.text() //we only get here if there is no error }) if (typeof xml_data_bdm == 'string') i = 10 } // 2 - analyse de la réponse XML let xml_tree = (new DOMParser).parseFromString(xml_data_bdm, "application/xml") let nodes = d3.hierarchy(xml_tree) let attrs_err = nodes.descendants().filter(d => d.data.tagName == "mes:Error") if (attrs_err.length == 1) { let errMsg = nodes.descendants().filter(d => d.data.tagName == "com:Text") console.log('error', errMsg[0].data.innerHTML) return {tb: aq.table({errMsg: [errMsg[0].data.innerHTML]}), errMsg:"Aucun résultat ne correspond à cette requête"} } // 3 - lecture des métadonnées générales (titre, unité...) let series = nodes.descendants().filter(d => d.data.tagName == "Series"), meta_headers = chartHeaders(series, !!spread_dimension) // 4 - lecture des données de base (TIME_PERIOD et OBS_VALUE) enrichies de quelques attributs let a = ((spread_dimension || multi_geo) ? nodes.descendants() : series[series.length-1].children) .filter(d => d.data.tagName == "Obs") .map(d=> { return {TIME_PERIOD:d.data.getAttribute("TIME_PERIOD"), OBS_VALUE: +d.data.getAttribute("OBS_VALUE"), REF_AREA: d.parent.data.getAttribute('REF_AREA'), IDBANK: d.parent.data.getAttribute('IDBANK'), DATASET: idbankToDtsMap.get(d.parent.data.getAttribute('IDBANK')), [spread_dimension]: !spread_dimension ? null : d.parent.data.getAttribute(spread_dimension) || idbank_map.get(d.parent.data.getAttribute('IDBANK')), TITLE: d.parent.data.getAttribute("TITLE_FR"), UNIT_MULT: Math.pow(10, d.parent.data.getAttribute("UNIT_MULT")) }}) // 5 - résultat final : table de données et métadonnées return {tb:aq.from(a).select(aq.not('null')).orderby(aq.desc('TIME_PERIOD'), 'REF_AREA') .filter(d => +d.OBS_VALUE == d.OBS_VALUE), ...meta_headers} }50:T1a15,getBdmChart = async function(data, spread_dimension, dst_def) { vl.vega.formatLocale(locale); // prise en compte du formatage français des nombres (axe y) vl.vega.timeFormatLocale(locale); let idbank_row = idbanksList[viewof selectedIdbank.querySelector('select').selectedIndex]; // 1 - gestion du zoom automatique sur l'axe y en fonction de idbank_row.zoom == 1 let zoom_ckb = viewof chartZoom; if (idbank_row.zoom && !chartZoom[0]) { zoom_ckb.value = [1]; zoom_ckb.dispatchEvent(new Event("input")); zoom_ckb.querySelector('input').setAttribute('disabled', 'disabled'); return; } if (!idbank_row.zoom) zoom_ckb.querySelector('input').removeAttribute('disabled'); let yscale = chartZoom[0] == 1 ? { zero: false } : {}; // 2 - gestion de l'éclatement en plusieurs modalités (ex différentes courbes par tranche d'âge) let cl_tb, cl_eclat_map, fmt_eclat, lib_eclat, isOrigin = vl.selectPoint('isOrigin'); if (spread_dimension) { cl_tb = codelistMap.get(dst_def.indic_to_codelist.get(spread_dimension)); (fmt_eclat = id => cl_tb .params({ id }) .filter(d => d.id == id) .get('lib') .split(', ')), (lib_eclat = codelistLibMap .get(dst_def.indic_to_codelist.get(spread_dimension)) .split(' ') .filter(d => d.trim() != '')); if (lib_eclat.length > 2) lib_eclat = [lib_eclat.slice(0, lib_eclat.length / 2).join(' ')].concat( lib_eclat.slice(lib_eclat.length / 2).join(' ') ); isOrigin = vl .selectPoint('isOrigin') .fields(spread_dimension) .bind('legend'); } if (fmt_eclat) vl.vega.expressionFunction('fmt_eclat', fmt_eclat); // 3 - gestion adaptative du titre et de la source let title = data.extrait_title.split('-').filter(d => d.trim() != ''); if (title.length > 2) title = [title.slice(0, title.length / 2).join(' - ')].concat( title.slice(title.length / 2).join(' - ') ); let source = ['Source : Insee BDM', data.unite_str.substring(2)]; if (source[1].trim() == '') source.pop(); if (width > 600) source = source.join(' - '); // 4 - gestion dynamique des libellés de l'axe temporel aq.addFunction('convert_to_date', convertToDate, { override: true }); let dt = data.tb.derive({ t: d => op.convert_to_date(d.TIME_PERIOD) }); // t est un vrai champ de type Date let plage_an = d3.extent(dt.array('t'), d => d.getFullYear()), delta_an = plage_an[1] - plage_an[0]; // libelle l'axe X avec l'année ou le mois de changement de semestre (ou de trimestre) : 2020 juin(5) let label_fn = function(v) { if (v.getMonth() == 11) return v.getFullYear() + 1; if ((v.getMonth() + 1) % 6 == 0 && delta_an <= 15 && width > 500) return v.toLocaleString('fr', { month: 'short' }); if ((v.getMonth() + 1) % 3 == 0 && delta_an <= 8 && width > 500) return v.toLocaleString('fr', { month: 'short' }); return ''; }; vl.vega.expressionFunction('periodicite', () => delta_an > 15 || width < 500 ? 12 : 3 ); vl.vega.expressionFunction('label_fn', label_fn); let period = 'infra_an'; let x = vl .x() .fieldT('t') .axis({ labelAngle: 0, labelOverlap: true, labelFlush: false, tickCount: { interval: "month", step: 1 }, gridColor: { expr: "timeFormat(datum.value, '%m') % periodicite() == 0 ? '#eee' : '#fff'" }, tickOpacity: { expr: "label_fn(datum.value) != '' ? 1 : 0" }, gridDash: { expr: "timeFormat(datum.value, '%m') == '12' ? [] : [2,2]" }, labelExpr: "label_fn(datum.value)" }); if (parseInt(dt.get('TIME_PERIOD')) == dt.get('TIME_PERIOD')) { // périodicité annuelle period = 'an'; x = vl .x() .fieldT('t') .axis({ labelAngle: 0, labelOverlap: true, grid: true, gridColor: { expr: "timeFormat(datum.value, '%m') == '01' ? '#eee' : null" }, tickColor: { expr: "timeFormat(datum.value, '%m') == '01' ? '#ccc' : null" }, labelColor: { expr: "timeFormat(datum.value, '%m') == '01' ? 'black' : null" } }); } // 5 - gestion de la couleur des courbes, de la légende ordonnée et cliquable let c = vl.color(); if (spread_dimension) { let cx = vl .color() .fieldN(spread_dimension) .scale({ range: [ '#f4b84d', '#1e9b9e', 'firebrick', 'steelblue', '#AD7AA1', 'hotpink', 'olivedrab' ] }) .legend({ title: lib_eclat, titleAnchor: 'middle', symbolStrokeWidth: 3, symbolSize: 400, labelLimit: width < 500 ? 150 : 300, orient: width < 500 ? 'bottom' : 'right', columns: width < 500 ? 2 : 1, labelFontSize: 11, labelExpr: "fmt_eclat(datum.value)" }); if (idbank_row.sort) cx = cx.sort("-y"); c = c.if(isOrigin, cx).value('#ccc'); } // 5 - ajout d'une droite horizontale de référence (ex : indice base 100) let y0 = idbank_row.y0; let y_rule = idbank_row.hasOwnProperty('y0') ? vl.markRule({ size: 1, color: '#aaa' }).encode(vl.y().datum(y0)) : null; // 6 - assemblage des couches du graphique : courbes d'évolution et droite de référence let layers = [ vl .markLine({ point: data.tb.dedupe('TIME_PERIOD').numRows() < 20 && data.tb.dedupe('TIME_PERIOD').numRows() > 10, interpolate: 'monotone', size: 2, color: '#1e9b9e' }) .params(isOrigin) // add selections to plot .encode( x.title(null), vl .y() .fieldQ('OBS_VALUE') .title(null) .scale(yscale) .axis({ grid: true }), c, vl .opacity() .if(isOrigin, vl.value(1.0)) .value(0.4), vl.tooltip([ vl .tooltip() .fieldT('t') .title('période ') .format(period == 'an' ? '%Y' : '%m-%Y'), vl .tooltip() .fieldQ('OBS_VALUE') .format(',') .title('valeur ') ]) ) ]; if (y_rule) layers.unshift(y_rule); // 7 - rendu final return vl .layer(layers) .data(dt) .title({ anchor: width < 500 ? 'start' : 'middle', subtitlePadding: 10, text: title, subtitle: source, limit: width }) .width(width) .autosize({ type: "fit", contains: "padding" }) .height(350) .render({ renderer: 'svg' }); }51:T623,getDstDef = async function(id_dtf) { let id_dst = dtfToDst.get(id_dtf) const url = "https://bdm.insee.fr/series/sdmx/datastructure/FR1/" + id_dst // 1 - chargement et sécurisation let i = 0, xml_dst_bdm while (i++ <= 5) { xml_dst_bdm = await fetch(url) .then( response => { if (response.status == 429) { return {error: response.status, msg: response.text() } } return response.text() //we only get here if there is no error }) if (typeof xml_dst_bdm == 'string') i = 10 } // 2 - lecture de la réponse XML let nodes = d3.hierarchy((new DOMParser).parseFromString(xml_dst_bdm, "application/xml")) let codelists2 = nodes.descendants() .filter(d => d.data.tagName == "Ref" && d.data.getAttribute('class') == 'Codelist') let codelists = codelists2.map(d => d.data.getAttribute('id')) let indic_to_codelist = new Map( codelists2 .map(d => [d.parent.parent.parent.data.getAttribute('id'), d.data.getAttribute('id')]) ) let dimensions = nodes.descendants().filter(d => d.data.tagName == "str:Dimension" && d.data.getAttribute('id') ) .map(d => d.data.getAttribute('id')) let attributes = nodes.descendants().filter(d => d.data.tagName == "str:Attribute" ) .map(d => d.data.getAttribute('id')) // 3 - assemblage des divers concepts dans un objet JS return {id_dst, codelists, dimensions, attributes, indic_to_codelist} }52:T61b,import {getBrowserLocale, locale, titleCase } from '@ericmauviere/arquero-table-utils' /*function getBrowserLocale(options = {}) { const defaultOptions = { languageCodeOnly: false, }; const opt = { ...defaultOptions, ...options, }; const browserLocales = navigator.languages === undefined ? [navigator.language] : navigator.languages; if (!browserLocales) { return undefined; } let a = browserLocales.map(locale => { const trimmedLocale = locale.trim(); return opt.languageCodeOnly ? trimmedLocale.split(/-|_/)[0] : trimmedLocale; }); return a && a.length > 0 ? a[0] : 'fr' ; } locale = { return { decimal: ",", thousands: "\u00a0", grouping: [3], currency: ["", "\u00a0€"], minus: "\u2212", percent: "\u202f%", "dateTime": "%a %b %e %X %Y", "date": "%d-%m-%Y", "time": "%H:%M:%S", "periods": ["AM", "PM"], "days": [...Array(7).keys()].map(d => titleCase(new Date(Date.UTC(2000, 0, d+2)).toLocaleDateString('fr', { weekday: 'long' }))), "shortDays": [...Array(7).keys()].map(d => titleCase(new Date(Date.UTC(2000, 0, d+2)).toLocaleDateString('fr', { weekday: 'short' }))), "months": [...Array(12).keys()].map(d => titleCase(new Date(Date.UTC(2000, d, 1)).toLocaleString("fr", {month: "long"}))), "shortMonths": [...Array(12).keys()].map(d => titleCase(new Date(Date.UTC(2000, d, 1)).toLocaleString("fr", {month: "short"}))) }; } function titleCase(s) { return s[0].toUpperCase() + s.slice(1) ; }*/53:T8e0,chartHeaders = function(series, has_spread_dimension) { let last_serie = series[series.length-1] let extrait_title = last_serie.data.getAttribute("TITLE_FR") let extrait_last_update = new Date(last_serie.data.getAttribute("LAST_UPDATE")) let extrait_unite = last_serie.data.getAttribute("UNIT_MEASURE") let extrait_unite_mult = Math.pow(10, +last_serie.data.getAttribute("UNIT_MULT")).toLocaleString() if (extrait_unite_mult == 1) extrait_unite_mult = '' let cun = codelistMap.get('CL_UNITE') extrait_unite = cun.params({extrait_unite}).filter('d.id==extrait_unite').get('lib') let unite_str = (' - unité : ' + extrait_unite_mult + ' ' + extrait_unite).toLowerCase() if (['individus', 'sans objet', 'unités', 'nombre'].includes(extrait_unite.toLowerCase().trim()) ) unite_str = extrait_unite_mult == '' ? '' : (' - unité : ' + extrait_unite_mult ) if (has_spread_dimension && series.length > 1) { let extrait_title0 = series[0].data.getAttribute("TITLE_FR"), a0 = extrait_title0.split(' '), a1 = extrait_title.split(' '), a = [] a0.forEach((d,i)=> { if (d == a1[i]) a.push(d) }) if (a.join('') == "--") { a0 = extrait_title0.split('-').reverse(), a1 = extrait_title.split('-').reverse(), a = [] a0.forEach((d,i)=> { if (d == a1[i]) a.push(d) }) a = a.reverse().join('-').split(' ') } extrait_title = a.join(' ').replace(/\s+/g, ' ') .replace('Ensemble des ans', '') .replace('Ensemble des', '') .replace('Ensemble de', '') .replace('de ans de', '') .replace('à ans', '') .replace('ans', '') .replace('d la', 'dans la') .replace('d le', 'dans le') .replace('des femmes de', '') .replace('de à ans', "par classe d'âge") .replace('- -', '-') } return {extrait_title, extrait_last_update, extrait_unite, extrait_unite_mult, unite_str} }54:Tdad,dataflowsTb = { const url = "https://bdm.insee.fr/series/sdmx/dataflow"//"https://api.insee.fr/series/BDM/V1/dataflow/FR1/all" let i = 0, dtfs // 1 - sécurisation en cas de réponse dilatoire du serveur while (i++ <= 5) { dtfs = await fetch(url)//, get_fetch_options()) .then( response => { if (response.status == 429) { return {error: response.status, msg: response.text() } } return response.text() //we only get here if there is no error }) if (typeof dtfs == 'string') i = 10 } // 2 - conversion de la réponse XML en graphe JavaScript let nodes = d3.hierarchy((new DOMParser).parseFromString(dtfs, "application/xml")) let a = nodes.descendants().filter(d => d.data.tagName == "str:Dataflow") .map(d => { let lib = d.children.filter(e => e.data.tagName == "com:Name" && e.data.getAttribute('xml:lang') == 'fr') let serie = d.descendants().filter(e => e.data.tagName == "com:AnnotationText" && e.data.getAttribute('xml:lang') == 'fr') let dst = d.descendants().filter(e => e.data.tagName == "Ref") let url = d.descendants().filter(e => e.data.tagName == "com:AnnotationURL") return { id_dtf: d.data.getAttribute('id'), lib_dtf: lib.length == 1 ? lib[0].data.innerHTML : '', series: serie.length >= 1 ? +serie[0].data.innerHTML.match(/(?\d+)/, 'x')[0] : '', id_dst: dst.length >= 1 ? dst[0].data.getAttribute('id') : null, url : url.length >= 1 ? url[0].data.innerHTML : null } }) // 3 - exclusion de datasets comportant surtout des séries arrêtées return aq.from(a).orderby(aq.desc('series')) .filter(d => d.id_dtf != 'SERIES_BDM' && d.lib_dtf != '') .filter(d => !op.includes(d.id_dtf, 'CNA-2010')) .filter(d => !op.includes(d.id_dtf, 'CNT-2010')) .filter(d => !op.includes(d.id_dtf, 'CONSO-MENAGES-2010')) .filter(d => !op.includes(d.id_dtf, 'ICA-2005')) .filter(d => !op.includes(d.id_dtf, 'ICA-2010')) .filter(d => !op.includes(d.id_dtf, 'ICT-2012')) .filter(d => !op.includes(d.id_dtf, 'IP-PROD-CONS-N-HAB-2010')) .filter(d => !op.includes(d.id_dtf, 'IC-PROD-CONS-2010')) .filter(d => !op.includes(d.id_dtf, 'IPC-19')) .filter(d => d.id_dtf !== 'IPAGRI') .filter(d => !op.includes(d.id_dtf, 'IPCH-200')) .filter(d => !op.includes(d.id_dtf, 'IPEA-2010')) .filter(d => !op.includes(d.id_dtf, 'IPGD-19')) .filter(d => !op.includes(d.id_dtf, 'IPI-19') && !op.includes(d.id_dtf, 'IPI-200') && !op.includes(d.id_dtf, 'IPI-2010')) .filter(d => d.id_dtf !== 'IPLA-IPLNA-2010') .filter(d => !op.includes(d.id_dtf, 'IPPI-200') && !op.includes(d.id_dtf, 'IPPI-2010')) .filter(d => d.id_dtf !== 'IPPS-2010') .filter(d => d.id_dtf !== 'IPPMP') .filter(d => d.id_dtf !== 'IPPS-2015') .filter(d => d.id_dtf !== 'SALAIRES-ACEMO') .filter(d => d.id_dtf !== 'SERIES-LOYERS') .filter(d => d.id_dtf !== 'DETTE-TRIM-APU') .filter(d => d.id_dtf !== 'INDEX-BT-TP-DIV-ANCIENNES-BASES') .filter(d => d.id_dtf !== 'TCRED-ECONOMIE-PIB-REG-2014') }55:T140f,bdmChart = { vl.vega.formatLocale(locale) // prise en compte du formatage français des nombres (axe y) vl.vega.timeFormatLocale(locale) let yscale = chartZoom[0] == 1 ? {zero: false} : {} // 2 - gestion de l'éclatement en plusieurs modalités (ex différentes courbes par tranche d'âge) let cl_tb, cl_eclat_map, fmt_eclat, lib_eclat, isOrigin = vl.selectPoint('isOrigin') if (spreadDimension) { cl_tb = codelistMap.get(dstDef2.indic_to_codelist.get(spreadDimension)) fmt_eclat = id => cl_tb.params({id}).filter(d => d.id==id).get('lib').split(', '), lib_eclat = codelistLibMap.get(dstDef2.indic_to_codelist.get(spreadDimension)).split(' ') .filter(d => d.trim() != '') if (lib_eclat.length > 2) lib_eclat = [lib_eclat.slice(0,lib_eclat.length/2).join(' ')] .concat(lib_eclat.slice(lib_eclat.length/2).join(' ')) isOrigin = vl.selectPoint('isOrigin') .fields(spreadDimension) .bind('legend') } if (fmt_eclat) vl.vega.expressionFunction('fmt_eclat', fmt_eclat) // 3 - gestion adaptative titre et source let title = data.extrait_title.split('-').filter(d => d.trim() != '') if (title.length > 2) title = [title.slice(0,title.length/2).join(' - ')].concat(title.slice(title.length/2).join(' - ')) let source = ['Source : Insee BDM', data.unite_str.substring(2)] if (source[1].trim() == '') source.pop() if (width > 600 ) source = source.join(' - ') // 4 - gestion dynamique des libellés de l'axe temporel aq.addFunction('convert_toDate', convertToDate, { override: true }) let dt = data.tb.derive({t: d => op.convert_toDate(d.TIME_PERIOD) }) // t est un vrai champ de type Date let plage_an = d3.extent(dt.array('t'), d => d.getFullYear() ), delta_an = plage_an[1] - plage_an[0] // libelle année ou mois de changement de semestre : 2020 juin(5) let label_fn = function(v) { if (v.getMonth() == 11) return v.getFullYear() + 1 if ((v.getMonth() + 1) % 6 == 0 && delta_an <= 15) return v.toLocaleString('fr', {month:'short'}) if ((v.getMonth() + 1) % 3 == 0 && delta_an <= 8) return v.toLocaleString('fr', {month:'short'}) return '' } vl.vega.expressionFunction('periodicite', () => delta_an > 15 ? 12 : 3) vl.vega.expressionFunction('label_fn', label_fn) let x = vl.x().fieldT('t').axis({labelAngle: 0, labelOverlap: true, labelFlush: false, tickCount:{"interval": "month", "step": 1}, gridColor: {expr: "timeFormat(datum.value, '%m') % periodicite() == 0 ? '#ccc' : '#fff'"}, tickOpacity: {expr: "label_fn(datum.value) != '' ? 1 : 0"}, gridDash: {expr: "timeFormat(datum.value, '%m') == '12' ? [] : [2,2]"}, labelExpr: "label_fn(datum.value)"}) if ( parseInt(dt.get('TIME_PERIOD')) == dt.get('TIME_PERIOD') ) { x = vl.x().fieldT('t').axis({labelAngle: 0, labelOverlap: true, grid: true, gridColor:{expr: "timeFormat(datum.value, '%m') == '01' ? '#ccc' : null"}, tickColor:{expr: "timeFormat(datum.value, '%m') == '01' ? '#ccc' : null"}, labelColor:{expr: "timeFormat(datum.value, '%m') == '01' ? 'black' : null"}, }) } // 4 - gestion de la couleur des courbes, de la légende ordonnée et cliquable let c = vl.color() if (spreadDimension) { let cx = vl.color().fieldN(spreadDimension) .scale({range: ['#f4b84d', '#1e9b9e', 'firebrick', 'steelblue', '#AD7AA1', 'hotpink', 'olivedrab']}) .legend({title: lib_eclat, titleAnchor: 'middle', symbolStrokeWidth: 3, symbolSize: 400, labelFontSize: 11, labelExpr: "fmt_eclat(datum.value)"}) c = c.if(isOrigin, cx).value('#ccc') } // 6 - assemblage des couches du graphique : lignes et droite de référence let layers = [ vl.markLine({point: data.tb.dedupe('TIME_PERIOD').numRows() < 20 && data.tb.dedupe('TIME_PERIOD').numRows() > 10, interpolate: 'monotone', size:2, color:'#1e9b9e'}) .params(isOrigin) // add selections to plot .encode( x.title(null), vl.y().fieldQ('OBS_VALUE').title(null).scale(yscale).axis({grid:true}), c, vl.opacity().if(isOrigin, vl.value(1.0)).value(0.4), vl.tooltip().fieldQ('OBS_VALUE').format(',') ) ] // 7 - rendu final /*setTimeout(() => { window.dispatchEvent(new Event('resize')) }, 100)*/ return vl.layer(layers) .data(dt) .title({anchor:'middle', subtitlePadding: 10, text: title, subtitle: source}) .width(width) .autosize({ "type": "fit", "contains": "padding" }) .height(300) .render({renderer: 'svg'}) }56:Ta44,getBdmData2 = async function(url_sdmx, spread_dimension) { // 1 - acquisition des données, gestion des erreurs potentielles ou du quota let i = 0, xml_data_bdm while (i++ <= 5) { xml_data_bdm = await fetch(url_sdmx) .then( response => { if (response.status == 429) { return {error: response.status, msg: response.text() } } return response.text() //we only get here if there is no error }) if (typeof xml_data_bdm == 'string') i = 10 } let xml_tree = (new DOMParser).parseFromString(xml_data_bdm, "application/xml") let nodes = d3.hierarchy(xml_tree) let attrs_err = nodes.descendants().filter(d => d.data.tagName == "mes:Error") if (attrs_err.length == 1) { let errMsg = nodes.descendants().filter(d => d.data.tagName == "com:Text") console.log('error', errMsg[0].data.innerHTML) return {tb: aq.table({errMsg: [errMsg[0].data.innerHTML]}), errMsg:"Aucun résultat ne correspond à cette requête"} } // 2 - lecture des métadonnées générales (titre, unité...) let series = nodes.descendants().filter(d => d.data.tagName == "Series"), meta_headers = chartHeaders(series, !!spread_dimension) // 3 - lecture des données de base (TIME_PERIOD et OBS_VALUE) enrichies de quelques attributs let a = ((spread_dimension) ? nodes.descendants() : series[series.length-1].children) .filter(d => d.data.tagName == "Obs") .map(d=> { return {TIME_PERIOD:d.data.getAttribute("TIME_PERIOD"), OBS_VALUE: +d.data.getAttribute("OBS_VALUE"), REF_AREA: d.parent.data.getAttribute('REF_AREA'), IDBANK: d.parent.data.getAttribute('IDBANK'), DATASET: idbankToDtsMap.get(d.parent.data.getAttribute('IDBANK')), [spread_dimension]: !spread_dimension ? null : d.parent.data.getAttribute(spread_dimension), //|| idbank_map.get(d.parent.data.getAttribute('IDBANK')), TITLE: d.parent.data.getAttribute("TITLE_FR"), UNIT_MULT: Math.pow(10, d.parent.data.getAttribute("UNIT_MULT")) }}) // 4 - résultat final : table de données et métadonnées return {tb:aq.from(a).select(aq.not('null')).orderby(aq.desc('TIME_PERIOD'), 'REF_AREA') .filter(d => +d.OBS_VALUE == d.OBS_VALUE), ...meta_headers} }57:T682,dtfSliceMask = { let eclat_string = spreadDimension ? spreadableDimensionsDtfMap.get(spreadDimension).join('%2B') : null let s = dtfStructTb2.columnNames().slice(2) .map(d => { switch (d) { case 'INDICATEUR': return indic case dimensionVars[0]: return dimensionVars[0] == spreadDimension ? eclat_string : var2_lb case dimensionVars.length > 0 && dimensionVars[1]: return dimensionVars[1] == spreadDimension ? eclat_string : var3_lb case dimensionVars.length > 0 && dimensionVars[2]: return dimensionVars[2] == spreadDimension ? eclat_string : var4_lb case dimensionVars.length > 0 && dimensionVars[3]: return dimensionVars[3] == spreadDimension ? eclat_string : var5_lb case dimensionVars.length > 0 && dimensionVars[4]: return dimensionVars[4] == spreadDimension ? eclat_string : var6_lb case dimensionVars.length > 0 && dimensionVars[5]: return dimensionVars[5] == spreadDimension ? eclat_string : var7_lb case dimensionVars.length > 0 && dimensionVars[6]: return dimensionVars[6] == spreadDimension ? eclat_string : var8_lb //case 'REF_AREA': //return ref_areas[0] default: return '' }}).join('.') return s }58:T45b,spreadableDimensionsDtfMap = { let a = dimensionViews.filter(d => spreadableDimensionsMap.has(d.dim_name) && d.cl_tb) let b = new Map() a.forEach( (d,i) => { let target_codelists = spreadableDimensionsMap.get(d.dim_name), actual_codelist = d.cl_tb.columnArray('id') if ( !Array.isArray(target_codelists[0]) ) { if ( target_codelists.filter(x => !actual_codelist.includes(x)).length == 0 ) // target inclus dans actual b.set( d.dim_name, target_codelists ) } else { for (let k = 0; k < target_codelists.length; k++ ) { if ( target_codelists[k].filter(x => !actual_codelist.includes(x)).length == 0 ) b.set( d.dim_name, target_codelists[k] ) } } }) let v = [...b.keys()] // test d'indépendance des deux variables susceptibles d'éclatement let test = v.length <= 1 ? true : dtfStructTb2.groupby(v).count().dedupe(v[0]).dedupe(v[1]).numRows() > 1 if (!test) b.delete(v[0]) // je ne garde que la dernière return b }59:T575,// Chargement d'une codelist et stockage dans codelistMap getCodelist2 = async function(cl) { if (!cl) return false if (codelistMap.has(cl)) return codelistMap.get(cl) if (codelistMap.get(cl) === "fetching") return codelistMap.set(cl, "fetching") const url = "https://bdm.insee.fr/series/BDM/V1/codelist/FR1/" + cl let xml_codelist_bdm = await fetch(url).then( res => res.text() ) let nodes = d3.hierarchy((new DOMParser).parseFromString(xml_codelist_bdm, "application/xml")) let a = nodes.descendants().filter(d => d.data.tagName == "str:Code") .map(d => { return {id:d.data.getAttribute("id"), lib: d.children.filter(e => e.data.tagName == "com:Name" && e.data.getAttribute('xml:lang') == 'fr')[0].data.innerHTML, c: d.parent.data.getAttribute("id") }}) let b = nodes.descendants().filter(d => d.data.tagName == "str:Codelist") .map(d => d.children.filter(e => e.data.tagName == "com:Name" && e.data.getAttribute('xml:lang') == 'fr')[0].data.innerHTML) //console.log(b) codelistLibMap.set(cl, b[0]) let dt = aq.from(a) codelistMap.set(cl, aq.from(a)) // stockage sous forme d'une table Arquero return dt }5a:T5b3,getDstDef2 = async function(id_dtf) { let id_dst = dtfToDst.get(id_dtf) const url = "https://bdm.insee.fr/series/sdmx/datastructure/FR1/" + id_dst let xml_dst_bdm = await fetch(url).then( res => res.text() ) let nodes = d3.hierarchy((new DOMParser).parseFromString(xml_dst_bdm, "application/xml")) let attrs_err = nodes.descendants().filter(d => d.data.tagName == "mes:Error") /*if (attrs_err.length == 1) { mutable codelist_replay = 1 console.log('error') return }*/ let codelists = nodes.descendants().filter(d => d.data.tagName == "Ref" && d.data.getAttribute('class') == 'Codelist') .map(d => d.data.getAttribute('id')) let codelists2 = nodes.descendants() .filter(d => d.data.tagName == "Ref" && d.data.getAttribute('class') == 'Codelist') let indic_to_codelist = new Map( codelists2 .map(d => [d.parent.parent.parent.data.getAttribute('id'), d.data.getAttribute('id')]) ) let dimensions = nodes.descendants().filter(d => d.data.tagName == "str:Dimension" && d.data.getAttribute('id') ) .map(d => d.data.getAttribute('id')) let dimensions0 = dimensions.concat() let attributes = nodes.descendants().filter(d => d.data.tagName == "str:Attribute" ) .map(d => d.data.getAttribute('id')) return {id_dst, codelists, dimensions, dimensions0, attributes, indic_to_codelist} }5b:[{"id":"14ba7f21af1e96dd8cdece97e5001f91c61be88c9e8ce20734ba35a37f6f60f05f291148297a444db8182d73fc8a7f6dac1c9d97f8821c4ee69609a203a193de","href":"https://static.observableusercontent.com/files/14ba7f21af1e96dd8cdece97e5001f91c61be88c9e8ce20734ba35a37f6f60f05f291148297a444db8182d73fc8a7f6dac1c9d97f8821c4ee69609a203a193de","name":"202304_correspondance_idbank_dimension.csv","type":"text/csv","lastModified":1683634093841.467,"size":30899702}] 29:{"id":"4b835881845f9b36","slug":null,"title":"Retroingénérie de l'utilisation du Webservice avec D3","thumbnail":"8d5f35482f0cc43c40b1ec9414dca92e011b2a18c706b6bf1cb27b5c6ccecdc0","access_level":"public","create_time":"$D2023-05-09T10:13:07.062Z","update_time":"$D2026-01-26T15:06:51.491Z","view_time":null,"first_public_time":"$D2023-05-09T10:13:07.062Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"76739ff3d068a96c","login":"bpicod","name":"Benjamin Picod","avatar_url":"https://avatars-next.observableusercontent.com/6b375e8997394156ec3faf704d4b2748e1fed2651347f717e3e5988f3e84164a","tier":"starter_2024","bio":"Webmaster for INSEE (French National Institute of Statistics and Economic Analysis). 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https://www.insee.fr/fr/information/2862759","create_time":"$D2026-01-26T16:16:15.402Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"b0047ee932812541","login":"bpicod","name":"Benjamin Picod","avatar_url":"https://avatars-next.observableusercontent.com/6b375e8997394156ec3faf704d4b2748e1fed2651347f717e3e5988f3e84164a","tier":null}}],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Retroingénérie de l'utilisation du Webservice avec D3","cells":[{"id":0,"value":"# Retroingénérie de l'utilisation du Webservice avec D3","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":45,"value":"## 2- [API-WEB](https://observablehq.com/@ericmauviere/decouverte-de-l-api-web-banque-de-donnees-macroeconomiques-bdm)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"{\n let idbank = \"000067681\" // taux de mortalité infantile\n \n const url = \"https://bdm.insee.fr/series/sdmx/data/SERIES_BDM/\" + idbank\n\n return fetch(url).then( response => response.text() )\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"xmlNodelist = {\n\n let idbank = \"000067681\" // taux de mortalité infantile\n \n const url = \"https://bdm.insee.fr/series/sdmx/data/SERIES_BDM/\" + idbank\n\n let xml_string = await fetch(url).then( response => response.text() ) \n \n let xml_doc = (new DOMParser).parseFromString(xml_string, \"application/xml\") // XMLDocument\n\n console.log(\"Dépliez cet arbre :\", xml_doc)\n \n return d3.hierarchy(xml_doc).descendants() \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"serieData = {\n return xmlNodelist\n .filter(d => d.data.tagName == \"Obs\") \n .map(d => { return {TIME_PERIOD:d.data.getAttribute(\"TIME_PERIOD\"), \n OBS_VALUE: +d.data.getAttribute(\"OBS_VALUE\")}\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"viewof serie_dt = {\n let a = xmlNodelist\n .filter(d => d.data.tagName == \"Obs\") \n .map(d => { return {TIME_PERIOD: d.data.getAttribute(\"TIME_PERIOD\"), \n OBS_VALUE: +d.data.getAttribute(\"OBS_VALUE\"),\n IDBANK: d.parent.data.getAttribute(\"IDBANK\"), // remontée niveau parent\n OBS_STATUS: d.data.getAttribute(\"OBS_STATUS\"),\n OBS_QUAL: d.data.getAttribute(\"OBS_QUAL\"),\n OBS_TYPE: d.data.getAttribute(\"OBS_TYPE\")\n }\n })\n \n return Inputs.table(a, {locale: 'fr'})\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":25,"value":"$4a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":30,"value":"Inputs.table(dtfTb, {locale:'fr', sort:'series', reverse: true, \n format:{url : d => html`${d}`}})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"Inputs.table(await getCodelist(\"CL_PERIODICITE\"),\n {columns:['id','lib'], layout:'auto', maxWidth:'200px'})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":42,"value":"Inputs.table(await getCodelist(\"CL_INSTRUMENTS_BALANCE_PAIEMENTS\"), {columns:['id','lib'],layout:'auto'})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":33,"value":"codelistMap = new Map()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"codelistLibMap = new Map()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":78,"value":"## 4-[MISE EN CACHE](https://observablehq.com/@ericmauviere/stockage-cdn-proxy-du-fichier-de-reference-insee-bdm-idbanks)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":108,"value":"inseeZipUrl = \"https://www.insee.fr/fr/statistiques/fichier/2862759/202601_correspondance_idbank_dimension.zip\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":113,"value":"maxAge = 4 * 7 * 24 * 3600 // 4 semaines de mise en cache","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"csv = fetchp_txtfile_from_zip(inseeZipUrl, null, {maxAge})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":116,"value":"deploy(\"insee_bdm_idbanks_2023_06.csv\", async (req, res) => {\n res.header(\"Cache-control\", `public, max-age=${maxAge}`)\n res.header(\"Content-Type\", \"text/plain\")\n res.send(csv)\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":88,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":80,"value":"import { deploy } from '@endpointservices/serverless-cells'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":47,"value":"## 1- [PRESENTATION](https://observablehq.com/@ericmauviere/presentation-de-la-banque-de-donnees-macroeconomiques-bdm-insee)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":60,"value":"viewof selectedIdbank = {\n let s = Inputs.select(idbanksList, {format: d => d.lib, width:'100%', valueof: d => d.idbanks}) \n \n s.style[\"max-width\"] = \"600px\"\n \n return s\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":155,"value":"bdm_chart_idbank = {\n if (data_id_bank.tb.errMsg) \n return md`**${data_id_bank.tb.errMsg}**`\n \n else \n return getBdmChart(data_id_bank.tb, data_id_bank.spread_dimension, data_id_bank.dst_def)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":164,"value":"export_buttons2 = {\n if (data_id_bank.tb && !data_id_bank.tb.errMsg) \n return html`

\n ${viewof chartZoom}\n ${doc_idbank}\n

\n ${DOM.download(new Blob([d3.csvFormat(data_id_bank.tb.tb.objects())], {type: \"text/csv\"}), \"data.csv\", \"CSV\")}\n \n ${DOM.download(await serialize(bdm_chart_idbank), \"bdm\", \"SVG\")}\n

\n`\n return md`

`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":167,"value":"Inputs.table(data_id_bank.tb.tb, {locale:'fr', layout:'auto'})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":170,"value":"viewof idDtf = {\n \n let s = Inputs.select(\n dataflowsTb.orderby('id_dtf')\n .semijoin(idbanksDt, ['id_dtf','famille'])\n .derive({libext_dtf: d => d.id_dtf + ' - ' + d.lib_dtf})\n .rollup({ map: op.map_agg('libext_dtf', 'id_dtf') }).get('map'), {label: 'Dataset :', width: 600})\n \n s.style.setProperty('--label-width', \"60px\")\n \n return s\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":173,"value":"md `**${dstDef.dimensions.length}** dimensions et **${dtfStructTb.numRows().toLocaleString()}** séries dans ce dataset : `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":175,"value":"viewof dtfStructTb = {\n let dims = dstDef.dimensions\n\n\n return idbanksDt.params({idDtf, dims})\n .filter(d => d.famille == idDtf)\n\n .derive({spread: d => op.split(d.list_mod, '.')})\n .spread('spread', { as: dims })\n\n .select(aq.not('list_mod', 'list_var'))\n .rename({famille:'DATASET', idbank: 'IDBANK'})\n \n .view(5000)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":201,"value":"{\n cls0\n return Inputs.table(idbanksDt.derive({INDICATEUR: d => op.split(d.list_mod, '.')\n [op.indexof(op.split(d.list_var, '.'), 'INDICATEUR')]})\n .derive({spread: d => op.split(d.list_mod, '.')})\n .spread('spread')\n .groupby('famille','INDICATEUR', 'spread_1').count()\n .lookup(codelistMap.get('CL_INDICATEUR'), ['INDICATEUR','id'], 'lib')\n .select('famille', {'spread_1':'FREQ'}, {'count':'SERIES'},{'lib':'INDICATEUR'})\n .rename({famille:'DATASET'})\n .orderby(0,1)\n , {locale: 'fr', layout: 'auto'})\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":210,"value":" {\n if (nivgeo == 'dept') return html`\n${viewof nivgeo}\n${viewof deptLb}\n\n`\n else return html`\n${viewof nivgeo}\n${viewof regLb}\n\n`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":237,"value":"viewof selIdbank = curcodgeo ? Inputs.table(dataIdBanksGeo.tb.orderby('IDBANK', 'TIME_PERIOD'), {locale:'fr', layout:'auto', required:false, multiple: false}) : Object.assign(md `

`, {value:0})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":248,"value":"curcodgeo ? md `${DOM.download(new Blob([dataIdBanksGeo.tb.toCSV({delimiter:';'})], {type: \"text/csv\"}), \"datageo.csv\", `Export CSV (${dataIdBanksGeo.tb.numRows().toLocaleString()} lignes)`)}` : md `

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":58,"value":"$4d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":56,"value":"cls0 = Promise.all([getCodelist(\"CL_UNITE\"), getCodelist(\"CL_ZONE_GEO\"), getCodelist(\"CL_INDICATEUR\")]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":139,"value":"$4e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":137,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":153,"value":"$50","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":179,"value":"dstDef = getDstDef(idDtf)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":127,"value":"$51","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":162,"value":"doc_idbank = {\n let d = data_id_bank.tb && !data_id_bank.tb.errMsg ? md `\nDoc. Insee\n`\n : md`

` \n d.style.display = 'inline-block'\n d.style.margin='0'\n return d\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":146,"value":"viewof chartZoom = {\n let c = Inputs.checkbox([ {id:1, lib:'Zoom axe Y'}], {value:0, format: x => x.lib, valueof : x => x.id})\n c.style.display = 'inline-flex'\n return c\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":65,"value":"import { aq, op } from '@uwdata/arquero'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":157,"value":"import {rasterize, serialize} from \"@mbostock/saving-svg\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":148,"value":"$52","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":144,"value":"convertToDate = function(time) {\n let a = time.split('-'), d\n if (a.length == 1) {\n d = new Date(time, 0, 1)\n //d.setDate(d.getDate() - 1)\n return d\n }\n \n if (a[1].substring(0,1) == \"Q\") {\n return new Date( a[0], (+a[1].substr(1)) * 3 - 1)\n }\n \n if (a[1].substring(0,1) == \"S\") {\n return new Date( a[0], (+a[1].substr(1)) * 6 - 1)\n }\n \n d = new Date(a[0], +a[1] - 1)\n\n return d\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":132,"value":"$53","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":231,"value":"dataIdBanksGeo = {\n if (!idbanksGeo ) return null\n const url = \"https://bdm.insee.fr/series/sdmx/data/SERIES_BDM/\" + idbanksGeo.join('%2B')\n\n return getBdmData(url, true, null)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":226,"value":"idbanksGeo = {\n if (!curcodgeo) return null \n \n return idbanksDt.params({curcodgeo})\n .filter(d => op.includes(d.famille, 'TCRED-'))\n .filter(d => op.includes(d.list_mod, `.${curcodgeo}.`))\n .array('idbank') \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":204,"value":"depts = cls0 ? codelistMap.get('CL_ZONE_GEO')\n .filter(d => op.substring(d.id,0,1) == 'D').select(0,1) : null","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":206,"value":"regs = {\n if (!cls0) return ;\n \n let regs2016 = ['01', '02', '03', '04', '06', '11', '24', '27', '28', '32', '44', '52', '53', '75', \n '76', '84', '93', '94'].map(d => 'R' + d)\n \n return codelistMap.get('CL_ZONE_GEO').params({regs2016})\n .filter(d => op.includes(regs2016, d.id))\n .derive({lib: d => op.substring(d.id,1) + ' - ' + d.lib})\n .select(0,1)\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":214,"value":"viewof deptLb = Inputs.select(aq.from([{id:null, lib:'Choisissez...'}]).concat(depts), \n {value: \"D01\", format: d => d.lib, valueof: d => d.id}) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":212,"value":"viewof regLb = Inputs.select(aq.from([{id:null, lib:'Choisissez...'}]).concat(regs), \n {value: 'R11', format: d => d.lib, valueof: d => d.id}) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":208,"value":"viewof nivgeo = Inputs.radio(new Map([[\"Département\", 'dept'], [\"Région\", \"reg\"]]), {value: \"dept\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":224,"value":"curcodgeo = nivgeo == 'dept' ? deptLb : regLb","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":123,"value":"dtfToDst = dataflowsTb.rollup({ map: op.map_agg('id_dtf', 'id_dst') }).get('map')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":121,"value":"$54","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":135,"value":"idbankToDtsMap = idbanksDt.rollup({map: op.map_agg('idbank','famille')}).get('map')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":72,"value":"idbanksDt = aq.loadCSV(\"https://webcode.run/observablehq.com/d/4b835881845f9b36;insee_bdm_idbanks_2023_06.csv\", {parse:{idbank: String}})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":251,"value":"## 3-[PARCOURS DÉTAILLÉ](https://observablehq.com/@ericmauviere/parcours-extensif-de-la-banque-de-donnees-macroeconomiques-bdm)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":257,"value":"viewof idDtf2 = {\n let s = Select(dataflowsTb.derive({x : d => op.replace(op.normalize(d.lib_dtf, 'NFD'), /[\\u0300-\\u036f]/g, \"\"),\n y: d => op.split(d.id_dtf, \"-\")[0]})\n .derive({libext_dtf: d => d.id_dtf + ' - ' + d.lib_dtf })\n .orderby('y', 'x')\n .rollup({ map: op.map_agg('libext_dtf', 'id_dtf') })\n .get('map'), {label: 'Dataset ', width: 600, value: 'CHOMAGE-TRIM-NATIONAL'})\n \n s.style.setProperty('--label-width', \"auto\")\n s.style.setProperty('max-width', \"700px\")\n\n return s //bind(s, viewof id_dtf)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":310,"value":"controls_panel = md `\n

${viewof indic}

${viewof var2_lb}

${viewof var3_lb}

${viewof var4_lb}

${viewof var5_lb}

${viewof var6_lb}

${viewof var7_lb}

${viewof var8_lb}

\n\n${spreadableDimensionsDtfMap.size > 0 ? md `

${viewof spreadDimension}

` : '' }\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":385,"value":"{\n return md `**${data.extrait_title}**
\n*Unité : ${(data.extrait_unite_mult.toLocaleString() + ' ' + data.extrait_unite.toLowerCase()).trim()}, \nDocumentation Insee, dernière mise à jour : ${data.extrait_last_update.toLocaleString('fr', {dateStyle: 'long'})}*\n`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":402,"value":"$55","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":410,"value":"viewof chart_zoom = Inputs.checkbox([ {id: 1, lib: \"Zoom sur l'axe Y\"}], \n {value: 0, format: x => x.lib, valueof : x => x.id})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":413,"value":"export_buttons = html`\n${DOM.download(new Blob([d3.csvFormat(data.tb.objects())], {type: \"text/csv\"}), \"data.csv\", \"Export CSV des données\")}\n${DOM.download(await serialize(bdmChart), \"bdm\", \"Export SVG\")}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":387,"value":"data = getBdmData2(`https://bdm.insee.fr/series/sdmx/data/${idDtf2}/${dtfSliceMask}`, spreadDimension)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":394,"value":"$56","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":389,"value":"$57","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":315,"value":"viewof spreadDimension = {\n \n let r = Radio([...spreadableDimensionsDtfMap.keys()]\n .concat(null), {label: \"Éclater par\", value: null,\n format : d => codelistLibMap.get(dstDef2.indic_to_codelist.get(d)) || \"..néant..\"\n })\n \n r.style.setProperty('--label-width', \"auto\")\n //r.style.setProperty('width', Math.min(700, width)+\"px\")\n \n return r\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":318,"value":"$58","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":324,"value":"dimensionViews = [viewof var2_lb, viewof var3_lb, viewof var4_lb, viewof var5_lb, viewof var6_lb, \n viewof var7_lb, viewof var8_lb]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":356,"value":"viewof var2_lb = dimensionSelectableCodelist([]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":359,"value":"viewof var3_lb = dimensionSelectableCodelist([var2_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":361,"value":"viewof var4_lb = dimensionSelectableCodelist([var2_lb, var3_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":363,"value":"viewof var5_lb = dimensionSelectableCodelist([var2_lb, var3_lb, var4_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":365,"value":"viewof var6_lb = dimensionSelectableCodelist([var2_lb, var3_lb, var4_lb, var5_lb])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":368,"value":"viewof var7_lb = dimensionSelectableCodelist([var2_lb, var3_lb, var4_lb, var5_lb, var6_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":370,"value":"viewof var8_lb = dimensionSelectableCodelist([var2_lb, var3_lb, var4_lb, var5_lb, var6_lb, var7_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":347,"value":"dimensionSelectableCodelist = function(mods) { // mods = listes précédentes\n let s, dim_name = dimensionVars[mods.length]\n \n if (dimensionVars.length <= mods.length) {\n s = Object.assign(html`

`, {value: null}) \n s.style.display = 'none'\n\n return s\n }\n\n let a = mods.map( (d, k) => d =='' || d === null ? '' : `d['${dimensionVars[k]}'] == '${d.split('%2B')[0]}'`)\n .filter(d => d != '' )\n \n let f = a.length > 0 ? '&& ' + a.join('&& ') : ''\n \n let p = dtfStructTb2.params({dim_name}).filter(\"d.INDICATEUR == indic\" + f)\n .dedupe(dim_name).columnArray(dim_name) //.filter(d => d != 'SO')\n\n if (p.length == 1) {//&& dim_name == 'REF_AREA'\n s = Object.assign(html`

`, {value: null, dim_name: null}) \n s.style.display = 'none'\n \n } else \n s = dimensionSelectableCodelist0(dim_name, p, this ? this.value : null)\n s.dim_name = dim_name\n\n return s\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":328,"value":"dimensionSelectableCodelist0 = function(dim_name, p, v) {\n cls\n \n if (dtfStructTb2.columnIndex(dim_name) < 0) return false \n \n let mods = dtfStructTb2.filter(d => d.INDICATEUR == indic) // codes effectivement utilisés dans ce dataset\n .dedupe(dim_name).columnArray(dim_name)\n\n if (mods.length <= 1) return false \n\n let cl_tb = codelistMap.get(dstDef2.indic_to_codelist.get(dim_name)) \n\n cl_tb = aq.table({id: p || mods})\n .join_left(cl_tb) \n\n if (dim_name == 'REF_AREA')\n cl_tb = cl_tb.derive({i: d => op.startswith(d.id, 'F') && op.length(d.id) < 3 ? \"\" : d.id}) \n .orderby('i')\n \n let s = Select(cl_tb, {label: codelistLibMap.get(dstDef2.indic_to_codelist.get(dim_name)) + \" \", value: v, \n format: d => d.lib || d.id, valueof: d => d.id}) \n \n s.cl_tb = cl_tb\n\n s.style.setProperty('--label-width', \"auto\")\n s.style.setProperty('max-width', \"700px\")\n \n return s\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":340,"value":"cls = Promise.all( dimensionVars.map(d => (getCodelist(dstDef2.indic_to_codelist.get(d)))) )","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":342,"value":"dimensionVars = {\n let excls = ['INDICATEUR', 'idbank', 'famille']\n let c_vars2 = dtfStructTb2.columnNames().filter(d => excls.indexOf(d) < 0)\n\n let a = c_vars2.map( dim_name => ({k: dim_name, s:dtfStructTb2.params({indic}).filter(d => d.INDICATEUR == indic)\n .dedupe(dim_name).array(dim_name)\n })\n )\n .filter(d => d.s.length > 1)\n .map(d => d.k)\n \n return a\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":344,"value":"viewof indic = {\n let s = Select(new Map(dtfStructure.INDICATEUR.map(d => [indicateursMap.get(d) || d, d])), \n {label: 'Indicateur ', width: 350})\n \n s.style.setProperty('--label-width', \"auto\")\n s.style.setProperty('max-width', \"700px\")\n \n return s\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":265,"value":"spreadableDimensionsMap = new Map([\n ['SEXE', ['1', '2']],\n ['AGE', [['00-24', '25-49', '50-'],\n ['15-24', '25-29', '30-34', '35-39', '40-50'], \n ['15-29', '30-44', '45-59', '70-74', '75-'], \n ['15-24', '25-49', '50-'],\n ['15-24', '25-49', '50-64']\n ]],\n ['PRIX_CONSO', ['PA-BOISSON', 'PA-VIANDES', 'PEH-TOTAL', '4002']],\n ['CATEGORIE_FP', ['A','B','C']],\n ['SECTEURS_LOYERS', ['SECTEUR_LIBRE','SECTEUR_SOCIAL']]\n])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":260,"value":"dtfStructTb2 = {\n let dims = dstDef2.dimensions,\n list_var = idbanksDt.params({idDtf2})\n .filter(d => d.famille == idDtf2).get('list_var').split('.')\n\n //dims = dims.slice(0, list_var.length)\n\n return idbanksDt.params({idDtf2, dims})\n .filter(d => d.famille == idDtf2)\n .filter(d => op.split(d.list_mod, '.')\n [op.indexof(op.split(d.list_var, '.'), 'SERIE_ARRETEE')] !== 'TRUE')\n .derive({spread: d => op.split(d.list_mod, '.')})\n .spread('spread', { as: dims })\n //.filter(d => d.famille !== 'CHOMAGE-TRIM-NATIONAL' || !d.REF_AREA || d.REF_AREA !== 'FM')\n .select(aq.not('list_mod', 'list_var'))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":285,"value":"dtfStructure = dstDef2.dimensions.reduce( (a,v) => {a[v] = dtfStructTb2.dedupe(v).array(v); return a}, {})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":282,"value":"indicateursMap = aq.from(await getCodelist2('CL_INDICATEUR'))\n .rollup({ map: op.map_agg('id', 'lib') }).get('map')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":406,"value":"$59","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":289,"value":"dstDef2 = getDstDef2(idDtf2)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":295,"value":"$5a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":253,"value":"import {Select, Table, Radio, Checkbox, bind} from \"@observablehq/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W5b","stdlib":"1"}} 24:null