28:null 29:["$","title",null,{"children":"n636 fr | Marc Thevenin | Observable"}] 2e:T678,graph1 = Plot.plot({ width: rWidth, height: rWidth>=900 ? 0.6*rWidth: rWidth>=600 ? rWidth*0.7: 350, marginTop: rWidth>600 ? 40 : 30, marginBottom: rWidth>900 ? 60 : rWidth>600 ? 40 : 30, marginLeft: rWidth>900 ? 100 : rWidth>600 ? 90 : 70, x: {tickFormat: "d", label: "Année", grid: true, labelArrow: false, labelAnchor:"center", ticks: rWidth>=900 ? 12: rWidth>600 ? 9 : 5}, y: {tickFormat: d=>d.toLocaleString(), domain: [1000000,3000000], ticks:8, grid: true, label: "Population", labelArrow: false }, marks: [ Plot.line(df1, {filter: d=> d.annee>=1861 && d.annee<=1926, x:"annee", y:"n", stroke: "#414141", strokeWidth: strokeW, curve: "catmull-rom"}), Plot.line(df1, {filter: d=> d.annee>=1926 && d.annee<2046, x:"annee", y:"n", stroke: "#414141", strokeWidth: strokeW, curve: "catmull-rom"}), Plot.line(df1, {filter: d=> d.annee>=1936 && d.annee<=2025, x:"annee", y:"n", stroke: "#414141", strokeWidth: strokeW, curve: "catmull-rom"}), Plot.dot(df1, {filter: d=> d.annee<2022, x:"annee", y:"n", fill: d=> d.var3===1 ? pal100[0] : pal100[3], stroke: "white", r: rWidth>900 ? 9 : rWidth>600 ? 7 :4, channels: { annee: {value: "annee", label: ""}, n: {value: "n", label: ""}, }, tip: { format: {z: false, y: false, x: false, fill: false, annee: "d", n: d=> `${d.toLocaleString()}`} , stroke: "transparent"}}), Plot.areaY(df1, {filter: d=> d.annee>=1926 && d.annee<=1936 ,x: "annee", y1: 1000000, y2: "n", curve: "catmull-rom", fill: pal100[0], fillOpacity:.15}), ] })2f:Ta33,boxPlotGraph1 = htl.html `

${viewof rWidth} ${cssLegend} ${title1} ${graph1}

Sandra Brée et l'équipe POPP, Population & Société, 636, Septembre 2025, Ined.

Sources : Annuaire statistique de la ville de Paris (différentes années). Insee.

`30:Tf27,graph2 = Plot.plot({ width: rWidth, height: rWidth>900 ? 0.6*rWidth : rWidth>600 ? .7*rWidth : 400 , marginTop: 40, marginLeft: rWidth>900 ? 60: rWidth>600 ? 50 : 40, marginBottom: rWidth>900 ? 60: rWidth>600 ? 50 : 40, marginRight:30, y: {label: "Age", ticks:10, grid: true, labelArrow: false, inset: 0, label: "Âge", domain:[0,105]}, x: {tickFormat: d=> Math.abs(d), domain: [-150,150], ticks:5, label:"Pour 10 000 habitants", labelArrow: false, labelAnchor:"center"}, color: {legend: false, domain: ["Paris", "France"], range: [pal100[0], "#999999"], marginLeft: 100}, marks: [ // paris Plot.line(df2b, {filter: d=> d.geo==="Paris" , x: "homme", y: "age", curve: "step"}), Plot.areaX(df2b, {filter: d=> d.geo==="Paris", x: "homme", y: "age", curve: "step", fill: pal100[0], fillOpacity: 1}), Plot.line(df2b, {filter: d=> d.geo==="Paris", x: "femme", y: "age", curve: "step",}), Plot.areaX(df2b, {filter: d=> d.geo==="Paris", x: "femme", y: "age", curve: "step", fill: pal100[0], fillOpacity: 1}), // france Plot.line(df2b, {filter: d=> d.geo==="France", x: "homme", y: "age", curve: "step", stroke: "#414141"}), Plot.areaX(df2b, {filter: d=> d.geo==="France", x: "homme", y: "age", curve: "step", fill: "#999999", fillOpacity: .3}), Plot.line(df2b, {filter: d=> d.geo==="France", x: "femme", y: "age", curve: "step", stroke: "#414141"}), Plot.areaX(df2b, {filter: d=> d.geo==="France", x: "femme", y: "age", curve: "step", fill: "#999999", fillOpacity: .3}), Plot.line(df2Tipb, {x:"n",y:"age", z: "z", curve: "step", stroke: "transparent", channels: { title: d=> `${d.geo}\n${d.sexe} de ${d.age} ans :\n${Math.round(Math.abs(d.n))} pour 10 000 `, geo: {value: "geo", label: ""}, sexe: {value: "sexe", label:""}, age: {value: "age", label:""}, n: {value: "n", label: ""} }, tip: {stroke: "transparent"} } ), // // bulles info // 4 Plot.text(["④"], {x:140, y:9, className: "bulle"}), Plot.dot(df2, {x: 140, y:9, fill: "transparent", channels: {title: d=>`Creux des naissances \nen raison de la \npremière guerre mondiale`}, tip: true} ), Plot.text(["④"], {x:-140, y:9, className: "bulle"}), Plot.dot(df2, {x: d=> -140, y:9, fill: "transparent", channels: {title: d=>`Creux des naissances \nen raison de la \npremière guerre mondiale`}, tip: true} ), // 3 Plot.text(["③"], {filter: d=> d.geo==="Paris",x:-140, y:20, className: "bulle"}), Plot.dot(df2b, {filter: d=> d.geo==="Paris" , x: -140, y:20, fill: "transparent", channels: {title: d=>`Paris: absence des hommes \nliée au service militaire \n(20 ans)`}, tip: true} ), Plot.text(df2b, {filter: d=> d.geo==="Paris" , x:-140, y:20, text: ["③"], className: "bulle"}), // 2 Plot.text(["②"], {x:-140, y:33, className: "bulle"}), Plot.dot(df2, {x: d=> -140, y:33, fill: "transparent", channels: {title: d=>`Décès masculin lors de la \npremière guerre mondiale`}, tip: true} ), // 1 Plot.text(["①"], {x:-140, y:54, className: "bulle"}), Plot.dot(df2, {x: d=> -140, y:54, fill: "transparent", channels: {title: d=>`Creux des naissances dû \nà la guerre franc-prussienne,\nau siège et à la \ncommune de Paris`}, tip: true} ), Plot.text(["①"], {x:140, y:54, className: "bulle"}), Plot.dot(df2, {x: d=> 140, y:54, fill: "transparent", channels: {title: d=>`Creux des naissances dû \nà la guerre franc-prussienne,\nau siège et à la \ncommune de Paris`}, tip: true} ), //Plot.ruleX([-150]), Plot.ruleX([0], {stroke: "white"}), Plot.ruleY([0], {stroke: "#414141"}), Plot.text(["Homme"], {x: -60, y: 105, tectAnchor: "end" }), Plot.text(["Femme"], {x: 60, y: 105, tectAnchor: "start" }), Plot.crosshairY(df2Tipb, {y: "age", dx:5, anchor: "right", ruleStrokeWidth:5}), ] })31:T468,comment = checknote===true ? html`

① Creux des naissances dû à la guerre franco-prussienne, au siège et à la Commune de Paris (1870-1871)

② Décès masculins lors de la première guerre mondiale

③ Paris : absence des hommes liée au service militaire (20 ans)

③ Creux des naissances en raison de la première guerre mondiale

`32:Te6b,boxPlotGraph2 = htl.html`

${viewof rWidth} ${cssLegend} ${cssToggle} ${title2}

${viewof legend2}

${graph2}

${viewof checknote} ${checknote===true ? comment : null}

Sandra Brée et l'équipe POPP, Population & Société, 636, Septembre 2025, Ined.

Sources : Résultats statistiques du recensement de la population (1926) et base Popp.

`33:T4f4,graph3a = Plot.plot({ width: rWidth, height: rWidth>900 ? 145 : rWidth>600 ? 150 : 125 , marginLeft: rWidth>900 ? 130 : rWidth>600 ? 100 : 70 , marginBottom: 0, marginTop: 0, marginRight: 25, y: {label: null, reverse: false, axis: false}, x: {label: null, domain: [0,100], grid: true, axis: false}, subtitle: "Hommes", fy: {label: null, padding: 0, tickFormat: "d"}, color: {legend: false, domain: domain, range:range}, marks: [ Plot.barX(df3a, {filter: d=> legend3.includes(d.conjFR) ,x: "n", y: "y", fill: "conjFR", fy: "annee", stroke: "black", channels: { conj: {value: "conjFR", label: ""}, annee: {value: "annee", label:""}, geo: {value: "value", label:""}, n: {value: "n", label: ""} }, tip: {format: {annee: "d", conjFR: true, n: d=> `${d}%` ,x: false, y: false, fill: false, fy: false}, stroke: "transparent"} }), Plot.text(["Paris"], {x: -1, y:1, textAnchor:"end", className:"zone" }), Plot.text(["France"], {x: -1, y:2, textAnchor:"end", className:"zone" }), Plot.axisFy({anchor: "left",x: -8, tickFormat:"d", textAnchor: "end", className:"annee"}), ] })34:T4f6,graph3b = Plot.plot({ width: rWidth, height: rWidth>900 ? 145 : rWidth>600 ? 150 : 125 , marginLeft: rWidth>900 ? 130 : rWidth>600 ? 100 : 70 , marginBottom: 0, marginTop: 0, marginRight: 25, y: {label: null, reverse: false, axis: false}, x: {label: null, domain: [0,100], grid: true, axis: false}, fy: {label: null, padding: 0, tickFormat: "d"}, color: {legend: false, domain: domain, range:range}, subtitle: "Femmes", marks: [ Plot.barX(df3b, {filter: d=> legend3.includes(d.conjFR) ,x: "n", y: "y", fill: "conjFR", fy: "annee", stroke: "black", channels: { conj: {value: "conjFR", label: ""}, annee: {value: "annee", label:""}, geo: {value: "value", label:""}, n: {value: "n", label: ""} }, tip: {format: {annee: "d", conjFR: true, n: d=> `${d}%` ,x: false, y: false, fill: false, fy: false}, stroke: "transparent"} }), Plot.text(["Paris"], {x: -1, y:1, textAnchor:"end", className:"zone" }), Plot.text(["France"], {x: -1, y:2, textAnchor:"end", className:"zone" }), Plot.axisFy({anchor: "left",x: -8, tickFormat:"d", textAnchor: "end", className:"annee"}), ] })35:T5a0,graph3c = Plot.plot({ width: rWidth, height: rWidth>900 ? 145 : rWidth>600 ? 150 : 100 , marginLeft: rWidth>900 ? 130 : rWidth>600 ? 100 : 70 , marginBottom: mBottom, marginTop: 0, marginRight: 25, subtitle: "Les deux sexes", y: { reverse: false, label: "Les deux sexes", labelAnchor:"top",labelArrow:false, tickSize:0}, x: {label: "%", domain: [0,100], grid: true, labelArrow: false}, fy: {label: null, padding: 0, tickFormat: "d",}, color: {legend: false, domain: domain, range:range}, marks: [ Plot.barX(df3c, {filter: d=> legend3.includes(d.conjFR) ,x: "n", y: "y", fill: "conjFR", fy: "annee", stroke: "black", order: ["Célibataires", "Pacsé.es", "Concubinage ou union libre", "Marié.es", "Veuves ou veufs", "Divorcé.es"], channels: { conj: {value: "conjFR", label: ""}, annee: {value: "annee", label:""}, geo: {value: "value", label:""}, n: {value: "n", label: ""} }, tip: {format: {annee: "d", conjFR: true, n: d=> `${d}%` ,x: false, y: false, fill: false, fy: false}, stroke: "transparent"} }), Plot.text(["Paris"], {x: -1, y:1, textAnchor:"end", className:"zone" }), Plot.text(["France"], {x: -1, y:2, textAnchor:"end", className:"zone" }), Plot.axisFy({anchor: "left",x: -8, tickFormat:"d", textAnchor: "end", className:"annee"}), ] })36:T112c,boxPlotGraph3 = htl.html `

${viewof rWidth} ${cssLegend} ${title3}

${viewof legend3}

${graph3a} ${graph3b} ${graph3c}

Sandra Brée et l'équipe POPP, Population & Société, 636, Septembre 2025, INED.

Champ : Personnes de 15 ans ou plus vivant en résidence habituelle à Paris et en France (hexagonale pour 1926 et 1936).

* En 1926 et 1936, les catégories correspondent aux états matrimoniaux stricts, les célibataires sont les personnes n’ayant jamais été mariées. En 2023, comme le concubinage (ou l’union libre) constitue une catégorie à part, la catégorie « célibataire » n’inclut pas les personnes vivant en couple.

Sources : Résultats statistiques du recensement de la population (1926 et 1936) et base Popp ; 2022 : https://www.insee.fr/fr/statistiques/2011101?geo=DEP-75#consulter-sommaire ; https://www.insee.fr/fr/statistiques/2011101?geo=FRANCE-1

`37:T69a,graph42 = { let map = viz.create({ domain: data4Map, width: rWidth>800 ? 0.9*rWidth: rWidth, projection: d3.geoConicConformal().center([2.454071, 46.279229]), zoomable: [1, 10], margin: 10 }); map.path({ data: data4Map, fill: "#e1e1e1", stroke: "white", strokeWidth: 1, filter: map.effect.shadow({ stdDeviation: 2, fill: "black", fillOpacity: 0.7, dx: 1, dy: 1 }) }); // on réutilise choroLeg (celui qui alimente déjà legendClasses) pour colorer ET filtrer map.path({ id: "choroLayer", data: data4Map2, fill: (d) => { const v = d.properties.n; const idx = legMap.classIndex(v); // -1 si valeur manquante if (idx === -1) return choroLeg.colorize(v); // données manquantes: comportement normal return legMap.has(idx) ? choroLeg.colorize(v) : legMap.deselectedColor; }, stroke: "white", strokeWidth: 1, filter: map.effect.shadow({ stdDeviation: 2, fill: "black", fillOpacity: 0.7, dx: 1, dy: 1 }) }); map.path({ data: arrondissements, fill: "transparent", stroke: "#313131", strokeWidth: strokeWMap }); map.path({ data: data4Map2, fill: "transparent", stroke: "transparent", strokeWidth: 1, tip: "Arrondissement: $c_ar \n\nQuartier : $l_qu \n\n$p%", tipstyle: { fontSize: 10, fill: "#414141", background: "white", stroke: "#414141", strokeWidth: 0, fontFamily: "poppins", fontWeight: "normal", fontStyle: "normal", textDecoration: "none", overOpacity: null, overFillOpacity: .7, overFill: "white", overStroke: "white", overStrokeOpacity: 1, overStrokeWidth: 1.5 } }); return map.render(); }38:Tda9,boxPlotGraph42 = htl.html `

${viewof rWidth} ${title4} ${viewof legMap} ${cssLegMap} ${graph42}

Sandra Brée et l'équipe POPP, Population & Société, 636, Septembre 2025, INED.

Source : Base de données Popp.

`39:Tadf,

Lieu de naissance	Paris 1926	France 1926	Paris 2020	France 2023
Dans le département de résidence* :	37,2	71,8	29,7	57,9
Paris	32,2		29,7
Dans une autre commune du département de la Seine*	5,0
Dans un autre département de France (hexagonale, en 1926)	51,9	22,4	45,3	29,0
Hors de France (hexagonale, en 1926)	10,9	5,8	25,0	13,1
Ensemble	100,0	100,0	100,0	100,0
* Jusqu’en 1968, Paris faisait partie du département de la Seine qui comptait deux autres arrondissements : Saint-Denis et Sceaux. *Sources* : Pour 1926, résultats statistiques du recensement de la population de 1926 et base de données Popp ; pour 2020-2023, Insee (https://www.insee.fr/fr/statistiques/8356264#tableau-figure2 ; https://www.insee.fr/fr/statistiques/3633212#tableau-infographie).

3a:Td7f,boxTab = html`

${titleTab} ${table}

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fr","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":9,"value":"pal100 = [\n \"#ff564e\", //rouge 0\n \"#ff7aad\", //rose 1\n \"#522673\", //mauve 2 \n \"#0042eb\", //bleu 3\n \"#5cd49e\", //vert 4 \n \"#ffb322\", //jaune 5\n \"#4f4f4f\", //gray 6\n \"#0036bc\", //blue dark 7\n \"#44ce90\", //green dark +40% 8\n \"#ff362d\", //red dark +10% 9\n \"#e6a527\", //dark yellow 10\n \n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"pal60 = [\n \"#ff9a96\", //rouge\n \"#ffb0cf\", //rose\n \"#987cac\", //mauve\n \"#678ef3\", //bleu\n \"#9ee5c5\", //vert\n \"#ffe597\", //jaune plus clair au pif\n \"#8a8a8a\", //noir\n 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Évolution de la population parisienne 1861-2025

Figure 2. Pyramides proportionnelles (pour 10 000) des populations parisienne et française en 1926

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Figure 3. Statuts conjugaux* des habitant·es de Paris et de France, en 1926, 1936 et en 2022

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Figure 4. Proportion de ménages avec employé·e(s) de maison vivant dans le logement, par quartier en 1926

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Tableau 1. Répartition (%) des habitant·es de Paris et de France selon leur lieu de naissance en 1926 et 2020-2023`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1681,"value":"$39","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"table","database":"$undefined"},{"id":2019,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1683,"value":"$3b","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"cssTab","database":"$undefined"},{"id":1886,"value":"quartierShort = FileAttachment(\"aaaa.geojson\").json()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1889,"value":"merge2 = viz.tool.merge({\n geom: quartierShort,\n geom_id: \"c_qu\",\n data: data4,\n data_id: \"c_qu\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1895,"value":"data4Map2 = merge2.featureCollection","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2026,"value":"viewof rWidth = {\n const div = html`
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