28:null 29:["$","title",null,{"children":"n642 FR | Marc Thevenin | Observable"}] 2e:T906,plot1 =Plot.plot({ width: rWidth, height: rWidth>900 ? 0.67*rWidth : width> 600 ? .72*rWidth : 450, marginTop: 50, marginLeft: rWidth>900 ? 140 : width>600 ? 120 : 80, marginBottom: width> 90 ? 60: width>600 ? 40 : 20 , color: {domain:["Solde naturel", "Solde migratoire"], range: [pal100[3], pal100[0]] }, x: {label: "Taux (pour 1 000 habitants)", labelArrow: false, grid: true, axis: true, axis: "both", domain: [-11,20], labelAnchor:"center"}, y: {label: null, grid: true}, marks: [ Plot.barX(df1, {filter: d=> legend1a.includes(d.indicFr) && d.indic !==3 && d.rang!=null , x:"t3", y:"paysFr", fill: "indicFr", order:"indic", // channels: {rang: {value: "rang"}}, sort : {y: tri==="Taux d'accroissement total" ? "rang3" : tri === "Solde naturel" ? "rang1" : "rang2" , reverse: false}, channels: { rang3: {value: "rang3"}, rang2: {value: "rang2", label: "Rang:"}, rang1: {value: "rang1", label: "Rang:"}, pays: {value: "paysFrFlag", label:""}, indic: {value: "indicFr", label:""}, n: {value: "t3", label:"",} }, tip: { format: {x:false, y: false, fill: false, rang: false, pays: true, indic: true, n: d=> `${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]) ] })2f: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.

`30: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" })) ] })31: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.

`32: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}) ] })33: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=> `${d.toFixed(1).replace(".",",")} millions` }, strokeWidth: 0} }), Plot.line(df3b, {filter: d=> d.annee>2022 , x: "annee", y: "n", stroke: "#ffe1a7", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5 }), Plot.line(df3b, {filter: d=> d.typeNum===1, x: "annee", y:"n", stroke: pal100[5], strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5}), Plot.line(df3b, {filter: d=> d.typeNum=== 2 , x: "annee", y: "n", stroke: "#ffe1a7", strokeWidth : width>900 ? 5: width>600 ? 3.5 : 2.5 } ), Plot.ruleY([0], {strokeWidth: .5}), Plot.text(["2023"], {x:2023, y:3.3}) ] })34:T85e,plot3c = Plot.plot({ width: rWidth, height: rWidth> 900 ? .6*rWidth : rWidth> 600 ? .61*rWidth : 300, marginTop: rWidth>900 ? 40 : rWidth> 600 ? 35 : rWidth>400 ? 30 : 20, marginLeft: rWidth>900 ? 50 : rWidth> 600 ? 40 : rWidth>400 ? 30 : 25, marginBottom: rWidth>900 ? 50 : rWidth> 600 ? 40 : 35, marginRight: rWidth>900 ? 30 : rWidth>600 ? 20 : 10, y: {ticks: width>600 ? [300,325,350,375,400,425,450,475,500] : [300,350,400,450,500], domain: [290,500], grid: true, label: "Millions d'habitants", labelArrow: false}, x: {domain: [1959,2050], ticks: width>600 ? [1960,1970,1980,1990,2000,2010,2020,2030,2040,2050] : [1960,1980,2000,2020,2040], tickFormat: "d", label: "Année", labelAnchor:"center", labelArrow:false, }, marks: [ Plot.frame({strokeWidth:.5}), Plot.ruleX(df3c, {x:2023, y1:290, y2:485, stroke: "#d1d1d1", strokeWidth:.5, lineAnchor: "bottom" }), Plot.line(df3c, {x: "annee", y:"n", z:"typeNum", stroke: "transparent", channels : { annee: {value: "annee", label: ""}, type: {value: "typeFr", label: ""}, n : {value : "n", label: "Habitants:"}, }, tip: {format: {x: false, y: false, z: false, annee:"d", type: true, n: d=> `${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}), ] })35: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.

`36:T978, 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FR","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1276,"value":"Lien vers G. Pison, Population & Sociétés, 642, mars 2026, Ined","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1279,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"pal100 = [\n \"#ff564e\", //rouge\n \"#ff7aad\", //rose\n \"#522673\", //mauve\n \"#0042eb\", //bleu\n \"#5cd49e\", //vert\n \"#ffb322\", //jaune\n \"#4f4f4f\", //gray\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":442,"value":"## Graphique 1","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":455,"value":"X = FileAttachment(\"n642_1@3.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":991,"value":"df1 = FileAttachment(\"n642_1@7.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":461,"value":"df1b = df1.filter(d=> d.pays!=null)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":546,"value":"domain = [\"Solde naturel\", \"Solde migratoire\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":549,"value":"range = [pal100[3], pal100[0]]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":571,"value":"#### Figure 2. Soldes naturel et migratoire dans les pays de l’Union européenne en 2024","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"title1","database":"$undefined"},{"id":1306,"value":"viewof legend1a = legend(domain, range, {selectAll: false, fontSize: \"clamp(11px,2cqw,15px\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":610,"value":"viewof tri = Inputs.select([\"Taux d'accroissement total\", \"Solde naturel\", \"Solde migratoire\" ], {label: \"Trier les pays par :\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":559,"value":"legend1b = Plot.legend({className:\"legend\", r: width>1000 ? 8 : width> 500 ? 6 : 4, symbol: { domain: [\"Taux d'accroissement total\"]}})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":458,"value":"$2e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":502,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":8,"value":"## Graphique 2","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":10,"value":"df2 = FileAttachment(\"n642_2@2.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"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","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"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","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":139,"value":"viewof yValue = Inputs.radio([\"Âge\", \"Année de naissance\"], {label: \"\", value: \"Âge\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":20,"value":"$30","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1349,"value":"viewof checknote = toggle({label:\"Afficher les commentaires\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":119,"value":" heightInfo = {\n let n; \n if (checknote===true && rWidth>=900) {return n=260}\n if (checknote===true && rWidth>=600) {return n=200} \n if (checknote===true && rWidth<600) {return n=150} \n {return n = 0}\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"info = Plot.plot({\nmarginTop:10, \nmarginBottom:0, \nmarginRight: 30,\nwidth: rWidth,\nheight: heightInfo, \nx: {domain: [0,10], axis: false}, \ny: {domain: [-1.7,4.5], axis: false},\n marks : [\n \n \nPlot.text([width>600 ? \"① Passage des classes creuses nées durant la guerre de 1914-1918 à l'âge de la fécondité\" : \"① Passage des classes creuses nées durant la guerre\\nde 1914-1918 à l'âge de la fécondité\" ], {x:0, y:4, textAnchor:\"start\", className: \"textBulle\"}),\n\nPlot.text([\"② Déficit des naissances dû à la guerre de 1939-1945\"], {x:0, y:2.8, textAnchor:\"start\", className: \"textBulle\"}),\n \nPlot.text([\"③ Baby-boom\"], {x:0, y:1.6, textAnchor:\"start\", className: \"textBulle\"}), \n\nPlot.text([\"④ Fin du baby-boom\"], {x:0, y:0.4, textAnchor:\"start\", className: \"textBulle\"}), \n\nPlot.text([\"⑤ Baisse de la fécondité\"], {x:0, y:-.8, textAnchor:\"start\", className: \"textBulle\"}), \n ]\n\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":255,"value":"

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

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

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