2f:T906,plot1 =Plot.plot({ width: rWidth, height: rWidth>900 ? 0.67*rWidth : width> 600 ? .72*rWidth : 450, marginTop: 50, marginLeft: rWidth>900 ? 140 : width>600 ? 120 : 80, marginBottom: width> 90 ? 60: width>600 ? 40 : 20 , color: {domain:["Solde naturel", "Solde migratoire"], range: [pal100[3], pal100[0]] }, x: {label: "Taux (pour 1 000 habitants)", labelArrow: false, grid: true, axis: true, axis: "both", domain: [-11,20], labelAnchor:"center"}, y: {label: null, grid: true}, marks: [ Plot.barX(df1, {filter: d=> legend1a.includes(d.indicFr) && d.indic !==3 && d.rang!=null , x:"t3", y:"paysFr", fill: "indicFr", order:"indic", // channels: {rang: {value: "rang"}}, sort : {y: tri==="Taux d'accroissement total" ? "rang3" : tri === "Solde naturel" ? "rang1" : "rang2" , reverse: false}, channels: { rang3: {value: "rang3"}, rang2: {value: "rang2", label: "Rang:"}, rang1: {value: "rang1", label: "Rang:"}, pays: {value: "paysFrFlag", label:""}, indic: {value: "indicFr", label:""}, n: {value: "t3", label:"",} }, tip: { format: {x:false, y: false, fill: false, rang: false, pays: true, indic: true, n: d=> `${d.toFixed(1).replace(".",",")} ‰`, rang1: true}, strokeWidth:0 } }), Plot.dot(df1, {filter: d=> d.indic ===3 && d.rang!=null, x:"t3", y:"paysFr", r: width>900 ? 6 : width> 600 ? 4 : 2, strokeWidth: width>600 ? 1 : .5, channels: { rang3: {value: "rang3", label: "Rang: "}, pays: {value: "paysFrFlag", label:""}, indic: {value: "indicFr", label:""}, n: {value: "t3", label:"",} }, tip: legend1a.length===0 ? {format: {x:false, y:false, rang: false, pays: true, indic: true, n: d=> `${d.toFixed(1).replace(".",",")}‰`, Rang3: true }, strokeWidth:0} : false }), Plot.ruleX([0]) ] })30:Tf13,boxPlotGraph1 = htl.html `

${viewof rWidth} ${title1} ${viewof legend1a} ${legend1b} ${cssLegend} ${viewof tri} ${plot1}

G. Pison, Population & Sociétés, 642, mars 2026, Ined.

Lecture : Au Portugal, en 2024, le solde migratoire est de + 13,4 ‰ ; le solde naturel est de – 3,2 ‰, et la population a augmenté de 10,2 ‰.

Notes : Le solde naturel est la différence entre le nombre de naissances et le nombre de décès. Le solde migratoire est la différence entre le nombre d’entrées et le nombre de sorties du territoire – il inclut éventuellement un ajustement statistique. Les pays sont classés par ordre décroissant du taux d’accroissement total.

Source : Eurostat, 2026, https://ec.europa.eu/eurostat/web/main/data/database.

`31:T1a73,plot2 = Plot.plot({ width: rWidth, height: rWidth>900 ? 0.60*rWidth : rWidth>600 ? 0.61*rWidth : 320 , marginTop: rWidth>600 ? 40 : 25, marginLeft: rWidth>600 ? 60: 40, marginBottom: rWidth>600 ? 60 : 35, marginRight: rWidth>900 ? 80 : rWidth>600 ? 60: 40, y: {reverse: yValue==="Âge" ? false: true, tickFormat: "d", tickPadding:10, ticks: yValue==="Âge" ? [0,10,20,30,40,50,60,70,80,90,100] : [2025,2015,2005,1995,1985,1975,1965,1955,1945,1935,1925], grid:true, label: yValue==="Âge" ? "Âge" : "Année de naissance" ,labelArrow: false, }, x: {ticks: width>500 ? [-500,-400,-300,-200,-200,-100,0,100,200,300,400,500] : [-500,-250,0,250,500], tickPadding:width>1000 ? 10: 1, tickFormat: d=> Math.abs(d), domain:[-500,500], grid: true, label: "Effectifs en milliers", labelAnchor:"center", labelArrow:false }, marks: [ Plot.line(df2b, {x: "homme", y: d=> yValue==="Âge" ? d.age : d.aNaissance, curve: "step", stroke:"#222330", strokeWidth:1}), Plot.line(df2b, {x: "femme", y: d=> yValue==="Âge" ? d.age : d.aNaissance, curve: "step", stroke:"#222330", strokeWidth:1}), Plot.areaX(df2b, {x: "homme", y: d=> yValue==="Âge" ? d.age : d.aNaissance, curve: "step", fill:pal100[0], fillOpacity: 0.8}), Plot.areaX(df2b, {x: "femme", y: d=> yValue==="Âge" ? d.age : d.aNaissance, curve: "step", fill:pal100[0], fillOpacity:0.8}), Plot.line(df2Tip, {x: "n", y: d=> yValue==="Âge" ? d.age : d.aNaissance, z:"sexe", curve: "step", stroke:"transparent", strokeWidth:2, channels: { sexe: {value: "sexe", label: ""}, aNaissance: {value: "aNaissance", label: ""}, age: {value: "age", label:""}, n: {value: "n", label:""} }, tip: {format: {x: false, y: false, z: false, sexe: true, aNaissance: d=> `Né en ${d.toString()}`, age: d=> `Âgé de ${d.toString()} ans`, n: d=> `${Math.abs(d)} 000`}, strokeWidth: 0 } }), // Notes //1 Plot.text(["①"], {x:300, y: d=> yValue==="Âge" ? 86 : 1939, className:"bulles" }), Plot.dot(df2b, {x: 300, y: d=> yValue==="Âge" ? 86 : 1939, fill: "transparent", channels: {title: d=>`Passage des classes creuses\nnées durant la guerre de \n1914-1918 à l'âge de la fécondité`}, tip : rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), Plot.text(["①"], {x:-300, y: d=> yValue==="Âge" ? 86 : 1939, className:"bulles" }), Plot.dot(df2b, {x: -300, y: d=> yValue==="Âge" ? 86 : 1939, fill: "transparent", channels: {title: d=>`Passage des classes creuses\nnées durant la guerre de \n1914-1918 à l'âge de la fécondité`}, tip : rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}}), //2 Plot.text(["②"], {x: 400, y: d=> yValue==="Âge" ? 82 : 1943, className:"bulles" }), Plot.dot(df2b, {x: 400, y: d=> yValue==="Âge" ? 82 : 1943, fill: "transparent", channels: {title: d=>`Déficit des naissances dû\nà la guerre de 1939-1945`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), Plot.text(["②"], {x: -400, y: d=> yValue==="Âge" ? 82 : 1943, className:"bulles" }), Plot.dot(df2b, {x: -400, y: d=> yValue==="Âge" ? 82 : 1943, fill: "transparent", channels: {title: d=>`Déficit des naissances dû\nà la guerre de 1939-1945`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), //3 Plot.text(["③"], {x:450, y: d=> yValue==="Âge" ? 78 : 1947, className:"bulles" }), Plot.dot(df2b, {x: 450, y: d=> yValue==="Âge" ? 78 : 1947, fill: "transparent", channels: {title: d=>`Baby-boom`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), Plot.text(["③"], {x:-450, y: d=> yValue==="Âge" ? 78 : 1947, className:"bulles" }), Plot.dot(df2b, {x: -450, y: d=> yValue==="Âge" ? 78 : 1947, fill: "transparent", channels: {title: d=>`Baby-boom`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), //4 Plot.text(["④"], {x:490, y: d=> yValue==="Âge" ? 51 : 1974, className:"bulles" }), Plot.dot(df2b, {x: 490, y: d=> yValue==="Âge" ? 51 : 1974, fill: "transparent", channels: {title: d=>`Fin du baby-boom`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), Plot.text(["④"], {x:-480, y: d=> yValue==="Âge" ? 51 : 1974, className:"bulles" }), Plot.dot(df2b, {x: -480, y: d=> yValue==="Âge" ? 51 : 1974, fill: "transparent", channels: {title: d=>`Fin du baby-boom`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), //5 Plot.text(["⑤"], {x:450, y: d=> yValue==="Âge" ? 5 : 2020, className:"bulles" }), Plot.dot(df2b, {x: 450, y: d=> yValue==="Âge" ? 5 : 2020, fill: "transparent", channels: {title: d=>`Baisse de la fécondité`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), Plot.text(["⑤"], {x:-450, y: d=> yValue==="Âge" ? 5 : 2020, className:"bulles" }), Plot.dot(df2b, {x: -450, y: d=> yValue==="Âge" ? 5 : 2020, fill: "transparent", channels: {title: d=>`Baisse de la fécondité`}, tip: rWidth<600 ? false : {fill: "#c8d7ff", fillOpacity:0.9, strokeWidth:0}} ), Plot.ruleX([0], {strokeWidth:1, stroke:"white", strokeWidth:1.5}) , Plot.text(["Hommes"], {x:-250, y: d=> yValue==="Âge" ? 103 : 1922, textAnchor:"end", lineAnchor:"bottom", fill:pal100[0]}), Plot.text(["Femmes"], {x:250, y: d=> yValue==="Âge" ? 103 : 1922, textAnchor:"start", lineAnchor:"bottom", fill:pal100[0]}), Plot.ruleY(df2b, Plot.pointerY({x1: -500, x2:500, y: d=> yValue==="Âge" ? d.age : d.aNaissance, stroke: "black"})), Plot.dot(df2Tip, Plot.pointerY({x: "n", y: d=> yValue==="Âge" ? d.age : d.aNaissance, stroke: "black", fill:"white"})), Plot.text(df2b, Plot.pointerY({x: 505, y: d=> yValue==="Âge" ? d.age : d.aNaissance, dy: -17, frameAnchor: "middle", textAnchor:"start", text: d=> yValue==="Âge" ? `Né en\n${d.aNaissance}` : `Âgé de\n${d.age} ans` , className:"pointer" })) ] })32:Tddb,boxPlotGraph2 = htl.html `

${viewof rWidth} ${title2}

Structure de la population par : ${viewof yValue}

${plot2}

${viewof checknote} ${info} ${cssToggle}

G. Pison, Population & Sociétés, 642, mars 2026, Ined.

Champ : France entière.

Source : Insee, estimations de population.

`33:Tfab,plot3a = Plot.plot({ width: rWidth, height: rWidth> 900 ? .6*rWidth : rWidth> 600 ? .61*rWidth : 300, marginTop: rWidth>900 ? 40 : rWidth> 600 ? 35 : rWidth>400 ? 30 : 20, marginLeft: rWidth>900 ? 50 : rWidth> 600 ? 40 : rWidth>400 ? 30 : 25, marginBottom: rWidth>900 ? 50 : rWidth> 600 ? 40 : 35, marginRight: rWidth>900 ? 30 : rWidth>600 ? 20 : 10, y: {ticks: width>600 ? [300,325,350,375,400,425,450,475,500] : [300,350,400,450,500], domain: [290,500], grid: true, label: "Millions d'habitants", labelArrow: false}, y: {tickFormat: d=> d.toFixed(1).replace(".",","), ticks: graph=== "Naissances et décès" && width>600 ? [3,3.5,4,4.5,5,5.5,6,6.5,7] : graph=== "Naissances et décès" && width<=600 ? [3,4,5,6,7] : graph=== "Solde naturel" && width>600 ? [-2,-1.5,-1,-0.5,0,0.5,1,1.5,2,2.5,3] : [-2,-1, 0 ,1,2,3], domain: graph === "Naissances et décès" ? [2.9,7] : [-2.3,3.5], grid: true, label: "Millions", labelArrow: false}, x: {domain: [1959,2050], ticks: width>600 ? [1960,1970,1980,1990,2000,2010,2020,2030,2040,2050] : [1960,1980,2000,2020,2040], tickFormat: "d", label: "Année", labelAnchor:"center", labelArrow:false, }, marks: [ Plot.frame({strokeWidth:.5}), Plot.ruleX(df3a, {x:2023, y1: graph==="Naissances et décès" ? 2.9 : -2.3, y2: graph==="Naissances et décès" ? 6.7 : 3.1, stroke: "#d1d1d1", strokeWidth:.5, lineAnchor: "bottom" }), // NAISSANCES & DECES graph === "Naissances et décès" ? Plot.line(df3aLong, { x: "annee", y:"n", z:"indic", stroke: "transparent", channels : { annee: {value: "annee", label: ""}, type: {value: "typeFr", label: ""}, indic: {value: "indic", label: ""}, n : {value : "n", label: ""}, }, tip: {format: {x: false, y: false, z: false, annee:"d", indic: true, type: true, n: d=> `${d.toFixed(1).replace(".",",")} millions` }, strokeWidth:0} }) : Plot.line(df3a, {x:"annee", y:"solde", stroke: "transparent", channels: { annee: {value: "annee", label: ""}, type: {value: "typeFr", label: ""}, n : {value : "solde", label: ""}, }, tip: {format: {x: false, y: false, annee:"d", type: true, n: d=> `${d.toFixed(1).replace(".",",")} millions` }, strokeWidth:0} }), //Observations graph === "Naissances et décès" ? Plot.line(df3aLong, {filter: d=> d.annee<2024, x: "annee", y: "n", z: "indic", stroke: d=> d.indic === "Naissances" ? pal100[0] : pal100[3], strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5}) : Plot.line(df3a, {filter: d=> d.annee<2024,x:"annee", y:"solde", stroke : "#33c081", strokeWidth : width>900 ? 8: width>500 ? 4 : 2.5, }), // Projections graph === "Naissances et décès" ? Plot.line(df3aLong, {filter: d=> d.annee>2022, x: "annee", y: "n", z: "indic", stroke: d=> d.indic === "Naissances" ? "#ffcecc" : "#acc4ff", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5}) : Plot.line(df3a, {filter: d=> d.annee>2022,x:"annee", y:"solde", stroke : "#ade9ce", strokeWidth : width>900 ? 8: width>500 ? 4 : 2.5, }), Plot.ruleY([0], {strokeWidth: .5}), Plot.text(["2023"], {x:2023, y: graph=== "Naissances et décès" ? 6.8 : 3.2}), Plot.text([graph==="Naissances et décès" ? "Épidémie\nde Covid-19" : ""], {x:2015,y:5.5, textAnchor:"end", lineAnchor:"bottom", className:"covid"}), Plot.arrow([1], { x1:2015.5, x2: 2020, y1:5.5, y2:5.31, bend: 20}) ] })34:T89f,plot3b = Plot.plot({ width: rWidth, height: rWidth> 900 ? .6*rWidth : rWidth> 600 ? .61*rWidth : 300, marginTop: rWidth>900 ? 40 : rWidth> 600 ? 35 : rWidth>400 ? 30 : 20, marginLeft: rWidth>900 ? 50 : rWidth> 600 ? 40 : rWidth>400 ? 30 : 25, marginBottom: rWidth>900 ? 50 : rWidth> 600 ? 40 : 35, marginRight: rWidth>900 ? 30 : rWidth>600 ? 20 : 10, marginRight: rWidth>600 ? 40 : 10, y: {ticks: width>600 ? [300,325,350,375,400,425,450,475,500] : [300,350,400,450,500], domain: [290,500], grid: true, label: "Millions d'habitants", labelArrow: false}, y: {ticks: [-1,-0.5,0,0.5,1,1.5,2,2.5,3,3.5], domain: [-1.1,3.5], grid: true, label: "Millions", labelArrow: false}, x: {domain: [1959,2050], ticks: width>600 ? [1960,1970,1980,1990,2000,2010,2020,2030,2040,2050] : [1960,1980,2000,2020,2040], tickFormat: "d", label: "Année", labelAnchor:"center", labelArrow:false, }, marks: [ Plot.frame({strokeWidth:.5}), Plot.ruleX(df3b, {x:2023, y1:-1.1, y2:3.2, stroke: "#d1d1d1", strokeWidth:.5, lineAnchor: "bottom" }), Plot.line(df3b, {x: "annee", y:"n", z:"typeNum", stroke: "transparent", channels : { annee: {value: "annee", label: ""}, type: {value: "typeFr", label: ""}, n : {value : "n", label: ""}, }, tip: {format: {x: false, y: false, z: false, annee:"d", type: true, n: d=> `${d.toFixed(1).replace(".",",")} millions` }, strokeWidth: 0} }), Plot.line(df3b, {filter: d=> d.annee>2022 , x: "annee", y: "n", stroke: "#ffe1a7", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5 }), Plot.line(df3b, {filter: d=> d.typeNum===1, x: "annee", y:"n", stroke: pal100[5], strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5}), Plot.line(df3b, {filter: d=> d.typeNum=== 2 , x: "annee", y: "n", stroke: "#ffe1a7", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5 } ), Plot.ruleY([0], {strokeWidth: .5}), Plot.text(["2023"], {x:2023, y:3.3}) ] })35:T85e,plot3c = Plot.plot({ width: rWidth, height: rWidth> 900 ? .6*rWidth : rWidth> 600 ? .61*rWidth : 300, marginTop: rWidth>900 ? 40 : rWidth> 600 ? 35 : rWidth>400 ? 30 : 20, marginLeft: rWidth>900 ? 50 : rWidth> 600 ? 40 : rWidth>400 ? 30 : 25, marginBottom: rWidth>900 ? 50 : rWidth> 600 ? 40 : 35, marginRight: rWidth>900 ? 30 : rWidth>600 ? 20 : 10, y: {ticks: width>600 ? [300,325,350,375,400,425,450,475,500] : [300,350,400,450,500], domain: [290,500], grid: true, label: "Millions d'habitants", labelArrow: false}, x: {domain: [1959,2050], ticks: width>600 ? [1960,1970,1980,1990,2000,2010,2020,2030,2040,2050] : [1960,1980,2000,2020,2040], tickFormat: "d", label: "Année", labelAnchor:"center", labelArrow:false, }, marks: [ Plot.frame({strokeWidth:.5}), Plot.ruleX(df3c, {x:2023, y1:290, y2:485, stroke: "#d1d1d1", strokeWidth:.5, lineAnchor: "bottom" }), Plot.line(df3c, {x: "annee", y:"n", z:"typeNum", stroke: "transparent", channels : { annee: {value: "annee", label: ""}, type: {value: "typeFr", label: ""}, n : {value : "n", label: "Habitants:"}, }, tip: {format: {x: false, y: false, z: false, annee:"d", type: true, n: d=> `${d.toFixed(1).replace(".",",")} millions`}, strokeWidth:0} }), Plot.line(df3c, {filter: d=> d.typeNum!==3, x: "annee", y:"n", stroke: "#9c5eca", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5}), Plot.line(df3c, {filter: d=> d.typeNum===1, x: "annee", y:"n", stroke: pal100[2], strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5}), Plot.line(df3c, {filter: d=> d.typeNum=== 3 , x: "annee", y: "n", stroke: "#cfb1e5", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5}), Plot.line(df3c, {filter: d=> d.typeNum=== 2 , x: "annee", y: "n", stroke: "#9c5eca", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5 } ), Plot.text(["2023"], {x:2023, y:490}), ] })36:Tfa2,boxPlotGraph3c = htl.html `

${viewof rWidth} ${title3} ${title3a}

${viewof graph}

${legend3a} ${plot3a} ${title3c} ${legend3c} ${plot3c} ${title3b} ${legend3b} ${plot3b}

G. Pison, Population & Sociétés, 642, mars 2026, Ined.

Champ : France entière.

Source : Source : Eurostat, 2025, Projections de population à court terme (2024-2050), https://ec.europa.eu/eurostat/databrowser/view/proj_stp25/default/table?category=proj.proj_23n.

`37:T978, 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2d:{"title":"n642 FR","cells":[{"id":0,"value":"# n642 FR","pinned":false,"hidden":false,"mode":"md"},{"id":1276,"value":"Lien vers G. Pison, Population & Sociétés, 642, mars 2026, Ined","pinned":false,"hidden":false,"mode":"md"},{"id":1279,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":5,"value":"pal100 = [\n \"#ff564e\", //rouge\n \"#ff7aad\", //rose\n \"#522673\", //mauve\n \"#0042eb\", //bleu\n \"#5cd49e\", //vert\n \"#ffb322\", //jaune\n \"#4f4f4f\", //gray\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":442,"value":"## Graphique 1","pinned":false,"hidden":false,"mode":"md"},{"id":455,"value":"X = FileAttachment(\"n642_1@3.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":991,"value":"df1 = FileAttachment(\"n642_1@7.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":461,"value":"df1b = df1.filter(d=> d.pays!=null)","pinned":false,"hidden":false,"mode":"ojs"},{"id":546,"value":"domain = [\"Solde naturel\", \"Solde migratoire\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":549,"value":"range = [pal100[3], pal100[0]]","pinned":false,"hidden":false,"mode":"ojs"},{"id":571,"value":"#### Figure 2. Soldes naturel et migratoire dans les pays de l’Union européenne en 2024","pinned":false,"hidden":false,"mode":"md"},{"id":1306,"value":"viewof legend1a = legend(domain, range, {selectAll: false, fontSize: \"clamp(11px,2cqw,15px\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":610,"value":"viewof tri = Inputs.select([\"Taux d'accroissement total\", \"Solde naturel\", \"Solde migratoire\" ], {label: \"Trier les pays par :\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":559,"value":"legend1b = Plot.legend({className:\"legend\", r: width>1000 ? 8 : width> 500 ? 6 : 4, symbol: { domain: [\"Taux d'accroissement total\"]}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":458,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":502,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"## Graphique 2","pinned":false,"hidden":false,"mode":"md"},{"id":10,"value":"df2 = FileAttachment(\"n642_2@2.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"df2b = df2.map(d=>({\nage: d.age,\naNaissance: d.aNaissance,\nfemme: d.femme,\nhomme: -d.homme,\nyNote: d.yNote,\nxNote: d.xNote \n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":74,"value":"df2Tip= yValue===\"Âge\" ? df2.flatMap(d => [\n {age: d.age, sexe: \"Homme\", n: -d.homme, aNaissance: d.aNaissance },\n {age: d.age, sexe: \"Femme\", n: d.femme, aNaissance: d.aNaissance},\n ])\n :\n df2.flatMap(d => [\n {aNaissance: d.aNaissance, sexe: \"Homme\", n: -d.homme, age: d.age },\n {aNaissance: d.aNaissance, sexe: \"Femme\", n: d.femme, age: d.age},\n ])","pinned":false,"hidden":false,"mode":"ojs"},{"id":139,"value":"viewof yValue = Inputs.radio([\"Âge\", \"Année de naissance\"], {label: \"\", value: \"Âge\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":20,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1349,"value":"viewof checknote = toggle({label:\"Afficher les commentaires\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":119,"value":" heightInfo = {\n let n; \n if (checknote===true && rWidth>=900) {return n=260}\n if (checknote===true && rWidth>=600) {return n=200} \n if (checknote===true && rWidth<600) {return n=150} \n {return n = 0}\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":122,"value":"info = Plot.plot({\nmarginTop:10, \nmarginBottom:0, \nmarginRight: 30,\nwidth: rWidth,\nheight: heightInfo, \nx: {domain: [0,10], axis: false}, \ny: {domain: [-1.7,4.5], axis: false},\n marks : [\n \n \nPlot.text([width>600 ? \"① Passage des classes creuses nées durant la guerre de 1914-1918 à l'âge de la fécondité\" : \"① Passage des classes creuses nées durant la guerre\\nde 1914-1918 à l'âge de la fécondité\" ], {x:0, y:4, textAnchor:\"start\", className: \"textBulle\"}),\n\nPlot.text([\"② Déficit des naissances dû à la guerre de 1939-1945\"], {x:0, y:2.8, textAnchor:\"start\", className: \"textBulle\"}),\n \nPlot.text([\"③ Baby-boom\"], {x:0, y:1.6, textAnchor:\"start\", className: \"textBulle\"}), \n\nPlot.text([\"④ Fin du baby-boom\"], {x:0, y:0.4, textAnchor:\"start\", className: \"textBulle\"}), \n\nPlot.text([\"⑤ Baisse de la fécondité\"], {x:0, y:-.8, textAnchor:\"start\", className: \"textBulle\"}), \n ]\n\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":255,"value":"

Figure 1. Population de la France - Évaluation provisoire au 1er janvier 2026

","pinned":false,"hidden":false,"mode":"html"},{"id":245,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":435,"value":"## Graphique 3","pinned":false,"hidden":false,"mode":"md"},{"id":868,"value":"

Figure 3. Naissances, décès, solde migratoire et population totale de l’Union européenne (à 27) depuis 1960 et projections jusqu’en 2050

","pinned":false,"hidden":false,"mode":"html"},{"id":774,"value":"## Graphique 3A","pinned":true,"hidden":false,"mode":"md"},{"id":777,"value":"df3a = FileAttachment(\"n642_3a@6.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":899,"value":"df3aLong = df3a.flatMap(d=> [\n {annee : d.annee, indic: \"Naissances\", n: d.naiss, type: d.typeNum, typeFr: d.typeFr, typeEn: d.typeEn},\n {annee : d.annee, indic: \"Décès\", n: d.deces, type: d.typeNum, typeFr: d.typeFr, typeEn: d.typeEn } \n ] \n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":877,"value":"viewof graph = Inputs.radio([\"Naissances et décès\", \"Solde naturel\"], {label: \"Graphique :\", value: \"Naissances et décès\"})","pinned":true,"hidden":false,"mode":"ojs"},{"id":783,"value":"##### a. Naissances et décès","pinned":false,"hidden":false,"mode":"md"},{"id":786,"value":"legend3a = Plot.legend({className:\"legend\", swatchWidth: 30, swatchHeight:4,\n columns: graph===\"Naissances et décès\" & width>600 ? 2 : 1,\n color: { \n domain: graph=== \"Naissances et décès\" ? [\"Naissances observées\", \"Naissances projetées\", \"Décès observés\", \"Décès projetés\"]\n : [\"Solde naturel observé\", \"Solde naturel projeté\"], \n range: graph === \"Naissances et décès\" ? [pal100[0], \"#ffcecc\", pal100[3], \"#acc4ff\"]\n : [\"#33c081\", \"#ade9ce\"] \n}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":817,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":834,"value":"## Graphique 3B","pinned":false,"hidden":false,"mode":"md"},{"id":836,"value":"df3b = FileAttachment(\"n642_3b@3.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":847,"value":"##### c. Solde migratoire","pinned":false,"hidden":false,"mode":"md"},{"id":838,"value":"legend3b = Plot.legend({className:\"legend\", swatchWidth: 30, swatchHeight:4, columns: 1, color: { domain: [\"Observations\", \"Projections (scénario central)\"], range: [pal100[5], \"#ffe1a7\"]}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":849,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":664,"value":"## Graphique 3C","pinned":false,"hidden":false,"mode":"md"},{"id":666,"value":"df3c = FileAttachment(\"n642_3c@6.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":723,"value":"##### b. Population","pinned":false,"hidden":false,"mode":"md"},{"id":759,"value":"legend3c = Plot.legend({className:\"legend\", swatchWidth: 30, swatchHeight:4, columns: 1, color: { domain: [\"Observations\", \"Projections (scénario central)\", \"Projections (scénario sans migrations)\"], range: [pal100[2], \"#9c5eca\", \"#cfb1e5\"]}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":668,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":712,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":215,"value":"$37","pinned":false,"hidden":false,"mode":"html"},{"id":1196,"value":"import {legend, cssLegend, toggle, cssToggle} from \"@wsthevenin/mtinput\"\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":1296,"value":"cssLegend","pinned":true,"hidden":false,"mode":"ojs"},{"id":1347,"value":"cssToggle","pinned":true,"hidden":false,"mode":"ojs"},{"id":1298,"value":"viewof rWidth = {\n const div = html`

`;\n const ro = new ResizeObserver(entries => {\n const w = entries[0].contentRect.width;\n if (w > 0 && w !== div.value) {\n div.value = w;\n div.dispatchEvent(new CustomEvent(\"input\"));\n }\n });\n ro.observe(div);\n div.value = div.getBoundingClientRect().width || 800;\n return div;\n} ","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W38","stdlib":"1","titling":"auto"}