25:["$","title",null,{"children":"Présentation de la banque de données macroéconomiques (BDM) de l'Insee | Benjamin Picod | Observable"}] 49:T141e,bdm_chart = { vl.vega.formatLocale(locale) // prise en compte du formatage français des nombres (axe y) vl.vega.timeFormatLocale(locale) let yscale = chart_zoom[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 = codelist_map.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 = codelist_lib_map.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 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_to_date', convert_to_date, { 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 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 (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, 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'}) }4a:Ta5e,get_bdm_data = 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, 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 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 = chart_headers(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: idbank_to_dts_map.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} }4b:T760,chart_headers = 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 = codelist_map.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) }) 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('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} }4c:Ta9e,dataflows_tb = { const url = "https://api.insee.fr/series/BDM/V1/dataflow/FR1/all" let dtfs = await fetch(url, get_fetch_options()).then( res => res.text() ) 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 ? +op.match(serie[0].data.innerHTML, /(?\d+)/, 'x') : '', id_dst: dst.length >= 1 ? dst[0].data.getAttribute('id') : null, url : url.length >= 1 ? url[0].data.innerHTML : null } }) 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') }4d:T464,spreadable_dimensions_dtf_map = { let a = dimension_views.filter(d => spreadable_dimensions_map.has(d.dim_name) && d.cl_tb) let b = new Map() a.forEach( (d,i) => { let target_codelists = spreadable_dimensions_map.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 : dtf_struct_tb.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 }4e:Td49,dtf_slice_mask = { let eclat_string = spread_dimension ? spreadable_dimensions_dtf_map.get(spread_dimension).join('%2B') : null let s = dtf_struct_tb.columnNames().slice(2) .map(d => { switch (d) { case 'INDICATEUR': return indic case dimension_vars[0]: return dimensiondtf_slice_mask = { let eclat_string = spread_dimension ? spreadable_dimensions_dtf_map.get(spread_dimension).join('%2B') : null let s = dtf_struct_tb.columnNames().slice(2) .map(d => { switch (d) { case 'INDICATEUR': return indic case dimension_vars[0]: return dimension_vars[0] == spread_dimension ? eclat_string : var2_lb case dimension_vars.length > 0 && dimension_vars[1]: return dimension_vars[1] == spread_dimension ? eclat_string : var3_lb case dimension_vars.length > 0 && dimension_vars[2]: return dimension_vars[2] == spread_dimension ? eclat_string : var4_lb case dimension_vars.length > 0 && dimension_vars[3]: return dimension_vars[3] == spread_dimension ? eclat_string : var5_lb case dimension_vars.length > 0 && dimension_vars[4]: return dimension_vars[4] == spread_dimension ? eclat_string : var6_lb case dimension_vars.length > 0 && dimension_vars[5]: return dimension_vars[5] == spread_dimension ? eclat_string : var7_lb case dimension_vars.length > 0 && dimension_vars[6]: return dimension_vars[6] == spread_dimension ? eclat_string : var8_lb //case 'REF_AREA': //return ref_areas[0] default: return '' }}).join('.') return s }Vars[0] == spread_dimension ? eclat_string : var2_lb case dimension_vars.length > 0 && dimension_vars[1]: return dimension_vars[1] == spread_dimension ? eclat_string : var3_lb case dimension_vars.length > 0 && dimension_vars[2]: return dimension_vars[2] == spread_dimension ? eclat_string : var4_lb case dimension_vars.length > 0 && dimension_vars[3]: return dimension_vars[3] == spread_dimension ? eclat_string : var5_lb case dimension_vars.length > 0 && dimension_vars[4]: return dimension_vars[4] == spread_dimension ? eclat_string : var6_lb case dimension_vars.length > 0 && dimension_vars[5]: return dimension_vars[5] == spread_dimension ? eclat_string : var7_lb case dimension_vars.length > 0 && dimension_vars[6]: return dimension_vars[6] == spread_dimension ? eclat_string : var8_lb //case 'REF_AREA': //return ref_areas[0] default: return '' }}).join('.') return s }4f:T5cd,get_dst_def = async function(id_dtf) { let id_dst = dtf_to_dst.get(id_dtf) const url = "https://api.insee.fr/series/BDM/V1/datastructure/FR1/" + id_dst let xml_dst_bdm = await fetch(url, get_fetch_options()).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} }50:T592,// Chargement d'une codelist et stockage dans codelist_map get_codelist = async function(cl) { if (!cl) return false if (codelist_map.has(cl)) return codelist_map.get(cl) if (codelist_map.get(cl) === "fetching") return codelist_map.set(cl, "fetching") const url = "https://api.insee.fr/series/BDM/V1/codelist/FR1/" + cl let xml_codelist_bdm = await fetch(url, get_fetch_options()).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) codelist_lib_map.set(cl, b[0]) let dt = aq.from(a) codelist_map.set(cl, aq.from(a)) // stockage sous forme d'une table Arquero return dt }51:[] 29:{"id":"aab09df8c42e425f","slug":null,"title":"Présentation de la banque de données macroéconomiques (BDM) de l'Insee","thumbnail":"4511f109e8a3c5798e2b64674e0083ed124dfab2791064a2ed8e093ae3bf8b99","access_level":"public","create_time":"$D2023-04-26T09:35:45.124Z","update_time":"$D2024-09-06T08:23:21.234Z","view_time":null,"first_public_time":"$D2023-04-26T09:35:45.124Z","has_unpublished_edits":null,"fork":{"id":"e81999e16ce22905","slug":"parcours-extensif-de-la-banque-de-donnees-macroeconomiques-bdm","title":"Présentation de la banque de données macroéconomiques (BDM) de l'Insee","owner":{"id":"cd09b02ddc62abda","login":"ericmauviere","name":"Éric Mauvière"}},"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). Interested in web based datavisualisation, libraries and tools.","following":false},"version":4402,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"b0047ee932812541","login":"bpicod","name":"Benjamin Picod","avatar_url":"https://avatars-next.observableusercontent.com/6b375e8997394156ec3faf704d4b2748e1fed2651347f717e3e5988f3e84164a","tier":null,"bio":"Webmaster for INSEE (French National Institute of Statistics and Economic Analysis). Interested in web based datavisualisation, libraries and tools.","following":false}],"members":[{"type":"individual","id":"b0047ee932812541","login":"bpicod","name":"Benjamin Picod","avatar_url":"https://avatars-next.observableusercontent.com/6b375e8997394156ec3faf704d4b2748e1fed2651347f717e3e5988f3e84164a","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Présentation de la banque de données macroéconomiques (BDM) de l'Insee","cells":[{"id":0,"value":"md`

Présentation de la banque de données macroéconomiques (BDM) de l'Insee

INSEE BDM › 3 - Parcours détaillé

\n\n# Parcours extensif de la banque de données macroéconomiques (BDM) de l'Insee\n\nLa BDM propose plus de 150 000 séries chronologiques, et vous pouvez pratiquement toutes les consulter et les visualiser ci-dessous !\n\nIl suffit de choisir un dataset, puis de jouer avec les dimensions et les modalités proposées. Parfois vous sera proposée la possibilité de voir ensemble plusieurs séries, déclinaison d'une même dimension.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1344,"value":"viewof id_dtf = {\n let s = Select(dataflows_tb.derive({x : d => op.replace(op.normalize(d.lib_dtf, 'NFD'), /[\\u0300-\\u036f]/g, \"\"),\n y: d => op.split(d.id_dtf, \"-\")[0]})\n .derive({libext_dtf: d => d.id_dtf + ' - ' + d.lib_dtf })\n .orderby('y', 'x')\n .rollup({ map: op.map_agg('libext_dtf', 'id_dtf') })\n .get('map'), {label: 'Dataset ', width: 600, value: 'CHOMAGE-TRIM-NATIONAL'})\n \n s.style.setProperty('--label-width', \"auto\")\n s.style.setProperty('max-width', \"700px\")\n\n return s //bind(s, viewof id_dtf)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2094,"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${spreadable_dimensions_dtf_map.size > 0 ? md `

${viewof spread_dimension}

` : '' }\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1551,"value":"{\n return md `**${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":3774,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1562,"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":"$undefined"},{"id":1907,"value":"export_buttons = html`\n${DOM.download(new Blob([d3.csvFormat(data.tb.objects())], {type: \"text/csv\"}), \"data.csv\", \"Export CSV des données\")}\n${DOM.download(await serialize(bdm_chart), \"bdm\", \"Export SVG\")}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":583,"value":"md `## Implémentation\n\nJe vous recommande de lire les [parties 1](https://observablehq.com/@ericmauviere/presentation-de-la-banque-de-donnees-macroeconomiques-bdm-insee) et [2](https://observablehq.com/@ericmauviere/decouverte-de-l-api-web-banque-de-donnees-macroeconomiques-bdm) de ce module de présentation de la BDM, avant que de tenter de plonger dans cette section plus obscure...\n### Fonctions données et graphique`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3304,"value":"data = get_bdm_data(`https://api.insee.fr/series/BDM/V1/data/${id_dtf}/${dtf_slice_mask}`, spread_dimension)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":846,"value":"$4a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1691,"value":"convert_to_date = function(time) {\n let a = time.split('-')\n if (a.length == 1) \n return new Date(time, 0, 1)\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 return new Date(a[0], +a[1] - 1)\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3802,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4265,"value":"md `### Liste des datasets / dataflows`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":672,"value":"dtf_struct_tb = {\n let dims = dst_def.dimensions,\n list_var = idbanks_dt.params({id_dtf})\n .filter(d => d.famille == id_dtf).get('list_var').split('.')\n\n //dims = dims.slice(0, list_var.length)\n\n return idbanks_dt.params({id_dtf, dims})\n .filter(d => d.famille == id_dtf)\n .filter(d => op.split(d.list_mod, '.')\n [op.indexof(op.split(d.list_var, '.'), 'SERIE_ARRETEE')] !== 'TRUE')\n .derive({spread: d => op.split(d.list_mod, '.')})\n .spread('spread', { as: dims })\n //.filter(d => d.famille !== 'CHOMAGE-TRIM-NATIONAL' || !d.REF_AREA || d.REF_AREA !== 'FM')\n .select(aq.not('list_mod', 'list_var'))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":660,"value":"idbanks_dt = aq.loadCSV(insee_csv_url, {parse:{idbank: String}}) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":460,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3799,"value":"idbank_to_dts_map = idbanks_dt.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":"$undefined"},{"id":2999,"value":"spread_dimension_index = {\n \n let lib_eclat = codelist_lib_map.get(dst_def.indic_to_codelist.get(spread_dimension))\n \n return dimension_views.findIndex( d => d.querySelector('label') ? \n d.querySelector('label').innerHTML.trim() == lib_eclat : false )\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2769,"value":"$4d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2332,"value":"spreadable_dimensions_map = 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":2413,"value":"$4e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":446,"value":"md `### dst datastructure`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":681,"value":"dtf_structure = dst_def.dimensions.reduce( (a,v) => {a[v] = dtf_struct_tb.dedupe(v).array(v); return a}, {})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1307,"value":"dimension_vars = {\n let excls = ['INDICATEUR', 'idbank', 'famille']\n let c_vars2 = dtf_struct_tb.columnNames().filter(d => excls.indexOf(d) < 0)\n\n let a = c_vars2.map( dim_name => ({k: dim_name, s:dtf_struct_tb.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":"$undefined"},{"id":647,"value":"dtf_to_dst = dataflows_tb.rollup({ map: op.map_agg('id_dtf', 'id_dst') }).get('map')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3327,"value":"dst_def = get_dst_def(id_dtf)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":434,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":448,"value":"md `### codelist` ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":991,"value":"$50","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1181,"value":"cls = Promise.all( dimension_vars.map(d => (get_codelist(dst_def.indic_to_codelist.get(d)))) )","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2790,"value":"codelist_lib_map = new Map()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":811,"value":"indicateurs_map = aq.from(await get_codelist('CL_INDICATEUR'))\n .rollup({ map: op.map_agg('id', 'lib') }).get('map') ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1767,"value":"cls0 = Promise.all([get_codelist(\"CL_UNITE\")]) //, get_codelist(\"CL_ZONE_GEO\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1150,"value":"codelist_map = new Map()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2076,"value":"md `### Gestion des listes déroulantes\nElles sont définies ici, mais ensuite déplacées pour piloter le graphique.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2285,"value":"dimension_selectable_codelist = function(mods) { // mods = listes précédentes\n let s, dim_name = dimension_vars[mods.length]\n \n if (dimension_vars.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['${dimension_vars[k]}'] == '${d.split('%2B')[0]}'`)\n .filter(d => d != '' )\n \n let f = a.length > 0 ? '&& ' + a.join('&& ') : ''\n \n let p = dtf_struct_tb.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 = dimension_selectable_codelist0(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":"$undefined"},{"id":1287,"value":"dimension_selectable_codelist0 = function(dim_name, p, v) {\n cls\n \n if (dtf_struct_tb.columnIndex(dim_name) < 0) return false \n \n let mods = dtf_struct_tb.filter(d => d.INDICATEUR == indic) // codes effectivement utilisés dans ce dataset\n .dedupe(dim_name).columnArray(dim_name)\n\n if (mods.length <= 1) return false \n\n let cl_tb = codelist_map.get(dst_def.indic_to_codelist.get(dim_name)) \n\n cl_tb = aq.table({id: p || mods})\n .join_left(cl_tb) \n\n if (dim_name == 'REF_AREA')\n cl_tb = cl_tb.derive({i: d => op.startswith(d.id, 'F') && op.length(d.id) < 3 ? \"\" : d.id}) \n .orderby('i')\n \n let s = Select(cl_tb, {label: codelist_lib_map.get(dst_def.indic_to_codelist.get(dim_name)) + \" \", value: v, \n format: d => d.lib || d.id, valueof: d => d.id}) \n \n s.cl_tb = cl_tb\n\n s.style.setProperty('--label-width', \"auto\")\n s.style.setProperty('max-width', \"700px\")\n \n return s\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3002,"value":"dimension_views = [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":"$undefined"},{"id":3203,"value":"dimension_values = [var2_lb, var3_lb, var4_lb, var5_lb, var6_lb, var7_lb, var8_lb]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2987,"value":"{\n dimension_views.forEach(d => d.querySelector('select') ? d.querySelector('select').removeAttribute('disabled') : true)\n \n if (spread_dimension_index >= 0) {\n dimension_views[spread_dimension_index].querySelector('select').setAttribute('disabled', 'disabled')\n }\n \n return \"Gestion des listes actives ou pas\"\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4315,"value":"md `Liste des indicateurs`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":735,"value":"viewof indic = {\n let s = Select(new Map(dtf_structure.INDICATEUR.map(d => [indicateurs_map.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":"$undefined"},{"id":2081,"value":"md `Listes des dimensions`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":819,"value":"viewof var2_lb = dimension_selectable_codelist([]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":822,"value":"viewof var3_lb = dimension_selectable_codelist([var2_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1239,"value":"viewof var4_lb = dimension_selectable_codelist([var2_lb, var3_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1406,"value":"viewof var5_lb = dimension_selectable_codelist([var2_lb, var3_lb, var4_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1882,"value":"viewof var6_lb = dimension_selectable_codelist([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":"$undefined"},{"id":2115,"value":"viewof var7_lb = dimension_selectable_codelist([var2_lb, var3_lb, var4_lb, var5_lb, var6_lb]) ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2946,"value":"viewof var8_lb = dimension_selectable_codelist([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":"$undefined"},{"id":2392,"value":"viewof spread_dimension = {\n \n let r = Radio([...spreadable_dimensions_dtf_map.keys()]\n .concat(null), {label: \"Éclater par\", value: null,\n format : d => codelist_lib_map.get(dst_def.indic_to_codelist.get(d)) || \"..néant..\"\n })\n \n r.style.setProperty('--label-width', \"auto\")\n //r.style.setProperty('width', Math.min(700, width)+\"px\")\n \n return r\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4188,"value":"md `### Connexion & librairies`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":466,"value":"//https://www.bdm.insee.fr/series/sdmx/codelist/\n//https://www.bdm.insee.fr/series/sdmx/dataflow/BALANCE-PAIEMENTS\n//https://www.insee.fr/fr/information/2860802\n//https://github.com/InseeFr/R-Insee-Data\n//https://www.oecd.org/development/pgd/1922938.pdf\ninsee_csv_zipped = \"https://www.insee.fr/fr/statistiques/fichier/2862759/202304_correspondance_idbank_dimension.zip\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":275,"value":"API_KEY = 'ea1f16b6-5a92-31e6-8b22-66f0028f5641'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1081,"value":"get_fetch_options = function() {\n return {\n headers: {\n Authorization: `Bearer ${API_KEY}`,\n 'Content-Type': 'text/xml; charset=UTF-8'\n }\n }\n //application/vnd.sdmx.structurespecificdata+xml;version=2.1 : format StructureSpecificData\n // application/vnd.sdmx.genericdata+xml;version=2.1 : format GenericData\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"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":"$undefined"},{"id":656,"value":"import {fetchp_txtfile_from_zip, getBrowserLocale, locale, titleCase } from '@ericmauviere/arquero-table-utils'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":342,"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":"$undefined"},{"id":1909,"value":"import {rasterize, serialize} from \"@mbostock/saving-svg\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2550,"value":"import {TimeChart, TimeAxis} from \"@observablehq/timechart\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2820,"value":"import {tuto_styles, toc} from '@ericmauviere/techniques-pour-tutoriels'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3532,"value":"endpoint = `@ericmauviere/stockage-cdn-proxy-du-fichier-de-reference-insee-bdm-idbanks`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3580,"value":"insee_csv_name = \"insee_bdm_idbanks_2022_10.csv\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3538,"value":"insee_csv_url = `https://webcode.run/observablehq.com/d/4b835881845f9b36;insee_bdm_idbanks_2023_06.csv`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1734,"value":"/*ref_areas = {\n let mods = [var2_lb, var3_lb, var4_lb, var5_lb, var6_lb, var7_lb, var8_lb], dim_name = 'REF_AREA'\n let a = mods.slice(0, dimension_vars.length)\n .map( (d,k) => d == '' ? '' : `d['${dimension_vars[k]}'] == '${d}'`)\n .filter(d => d != '')\n \n let f = a.length > 0 ? '&& ' + a.join('&&') : ''\n \n let p = dtf_struct_tb.params({dim_name}).filter(\"d.INDICATEUR == indic\" + f)\n .dedupe(dim_name).array(dim_name)\n \n console.log(p)\n \n return p\n}*/","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2819,"value":"tuto_styles","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W51","stdlib":"1"}} 24:null