28:null 29:["$","title",null,{"children":"n631: G1,2,3,5 | Marc Thevenin | Observable"}] 2e:T96c,plot1 = Plot.plot({ width: width, height: height, marginLeft:mLeft, marginRight: 40, marginTop: 45, marginBottom: mBottom, color: {legend: false, domain: ["Naissances", "Décès"], range: [color[0], color[2]]}, y: {label: "↑ Nombre (milliers)", grid: true, domain: [500,900], ticks: nticks, inset: 5}, x: {tickFormat: "d", label: "Année", domain: [1970, 2070], ticks: nticks}, //title: "Figure 1. Naissances et décès en France de 1970 à 2024 et projections jusqu’en 2070 (scénario « 2024 »)", marks: [ Plot.areaY(df1, {x: "année", y1: "décès", y2: "naissance", fill: "blue"}), // Naissances Plot.lineY(df1, {filter: d=> d.stat === "naissance" && d.type==="Observations" , x: "année", y: "n", stroke: color[0], strokeWidth: strokeW}), Plot.lineY(df1, {filter: d=> d.stat === "naissance" && d.type==="Projections" , x: "année", y: "n", stroke: color[0], strokeDasharray: [2,7], strokeWidth: strokeW }), // Décès Plot.lineY(df1, {filter: d=> d.stat === "décès" && d.type==="Observations" , x: "année", y: "n", stroke: color[2], strokeWidth: strokeW }), Plot.lineY(df1, {filter: d=> d.stat === "décès" && d.type==="Projections" , x: "année", y: "n", stroke: color[2], strokeDasharray: [2,7], strokeWidth: strokeW }), // artefact pour tip Plot.lineY(df1, {x: "année", y: "n", z: "statType", stroke: "transparent", channels: { année: {value: "année", label: "Année:"}, stat: {value: "stat", label: "Indicateur:"}, type: {value: "type", label: "Type:"}, n: {value: "n", label: "Nombre:" } }, tip: {format: {x:false, y: false, z: false, année: "d", n: (d) => `${d} 000` }, fontSize: 5} }), Plot.ruleX([2024.1], {y1: 500, y2: 900, strokeWidth:.5}), Plot.text(["Fin du baby boom"], {x: d =>1978, y: d=>860, lineWidth:6, textAnchor:"start"}), Plot.arrow([1],{x2: d=>1973, x1:d=>1977.5, y1: d=>870, y2: d=>870, bend: -20,}), Plot.text(["2024"], {x:d=>2024.1, y: d=>910}), //Plot.text(["↑ En milliers par an"], {x:1970, dx:-39, y:935, textAnchor:"start", fontSize:12}), Plot.ruleY([500]), Plot.ruleX([1970]), //Plot.axisY({dy:-5}) ] })2f:T616,plot2b = Plot.plot({ width: width, height:height, marginTop: 50, marginLeft: mLeft, marginRight:40, marginBottom: mBottom, x: {tickFormat: "d", label: "Année", grid: false, domain:[2021,2070], ticks:nticks}, y:{ grid: true, label: "Millions", domain: [55,80], ticks:nticks}, marks: [ Plot.lineY(data2, {x: "année", y: "n", z: "scenario", stroke: "transparent", strokeWidth:strokeW, channels:{ année: {value: "année", label: "Année:"}, scenario: {value: "scenario", label: "Scénario:"}, n: {value: "n", label: "Population:"}, }, tip: {format: {x: false, y: false, année: "d", z: false, n: (d) => `${d} millions`, }, fontSize: 12} }), Plot.line(data2, {filter: d=> d.scenario === "Scénario haut Insee 2021" ,x: "année", y: "n", stroke: color[6], strokeWidth: strokeW, strokeDasharray: [3,6]}), Plot.line(data2, {filter: d=> d.scenario === "Scénario 2024 auteurs" ,x: "année", y: "n", stroke: color[0], strokeWidth:strokeW}), Plot.line(data2, { filter: d => d.scenario ==="Scénario central Insee 2021",x: "année", y: "n", stroke: color[2], strokeWidth:strokeW}), Plot.line(data2, {filter: d => d.scenario ==="Scénario bas Insee 2021",x: "année", y: "n", stroke: color[7], strokeWidth:strokeW, strokeDasharray: [5,6]}) , Plot.ruleY([55]), Plot.ruleX([2021]) ] })30:T4fe,

Gilles Pison, Laurent Toulemon, Population & Sociétés, n° 631, mars 2025, Ined.
Notes:
Scénario central de l’Insee (2021) : fécondité constante de 1,8 enfant par femme, solde migratoire constant de + 70 000 par an, mortalité en diminution moyenne – au rythme de la décennie 2010.
Scénario « 2024 » (auteurs) : fécondité constante de 1,62 enfant par femme, solde migratoire constant de +152 000 par an (76 000 femmes et 76 000 femmes), mortalité en diminution faible : hypothèse basse de 2021 de l’Insee pour l’espérance de vie des femmes, hypothèse intermédiaire entre basse et moyenne pour celle des hommes (voir annexe en ligne).
Scénario « population haute » de l’Insee (2021) : fécondité constante de 2,0 enfants par femme, solde migratoire constant de +120 000 par an, mortalité en diminution forte.
Scénario « population basse » de l’Insee (2021) : fécondité constante de 1,6 enfant par femme, solde migratoire constant de +20 000 par an, mortalité en diminution faible.

31:T72c,plot3 = Plot.plot({ width: width, height:height, marginTop: 45, marginLeft:mLeft, marginRight:32, marginBottom:mBottom, color: {legend: false, domain: ["Femmes", "Hommes"], range: [color[5], color[3]]}, x: {tickFormat: "d", label: "Année", domain: [1994,2024], ticks: 5}, y: {grid: true, domain: [70,88], label: "↑ Espérance de vie", ticks: nticks, inset: 0}, marks: [ Plot.lineY(df3, { x: "années", y: "femmes", fontSize:14, stroke:color[5], strokeWidth: strokeW, channels: { années: {value: "années", label: "Année:"}, femmes: {value: "femmes", label: "Femmes:"}, }, tip: {format: {années: "d", y: false, x: false, femmes: (d) => `${d.toLocaleString("fr-FR")} ans`}, fontSize: 12} }), Plot.lineY(df3, { x: "années", y: "hommes", stroke:color[3], strokeWidth:strokeW, channels: { années: {value: "années", label: "Année:"}, hommes: {value: "hommes", label: "Hommes:"}, }, tip: {format: {années: "d", y: false, x: false, hommes: (d) => `${d.toLocaleString("fr-FR")} ans`}, fontSize: 12} }), Plot.text(["2003 Canicule"], {x: d =>2003, y: d=>79.25, fontSize: 10, lineWidth:6}), Plot.arrow([1],{x2: d=>2003, x1:d=>2003, y1: d=>78.1, y2: d=>75.9, bend: 0,}), Plot.arrow([1],{x2: d=>2003, x1:d=>2003, y1: d=>80.6, y2: d=>82.8, bend: 0,}), Plot.text(["2020 Covid-19"], {x: d =>2020, y: d=>82, fontSize: 12, lineWidth:6}), Plot.arrow([1],{x2: d=>2020, x1:d=>2020, y1: d=>83.2, y2: d=>85, bend: 0,}), Plot.arrow([1],{x2: d=>2020, x1:d=>2020, y1: d=>81, y2: d=>79.2, bend: 0,}), Plot.ruleY([70]), Plot.ruleX([1994]) ] }) 32:T663,plot5 = Plot.plot({ width: width, height:height, marginTop: 50, marginLeft:mLeft, marginRight:40, marginBottom:mBottom, x: {tickFormat:"d", domain: [1925,2021], label: "Année", ticks: nticks}, y: {domain:[0,900], grid: true, label: "↑ Nombre annuel de décès pour 10000 habitants*", ticks: nticks}, marks: [ Plot.line(df5, {filter: d=> d.type === "Cancers", x: "annee", y: "n", stroke: color[2], strokeDasharray: [2,6],strokeWidth: strokeW, }), Plot.line(df5, {filter: d=> d.type === "Cardiovasculaires", x: "annee", y: "n", stroke: color[0], strokeDasharray: [4,5], strokeWidth: strokeW, }), Plot.line(df5, {filter: d=> d.type === "Infectueuses et respiratoires" ,x: "annee", y: "n", stroke: color[4], strokeWidth: strokeW, }), // courbe transparent pour tip unique Plot.line(df5, {x: "annee", y: "n", stroke: "transparent", channels:{ annee: {value: "annee", label: "Année:"}, type: {value: "type", label: "Maladie:"}, n: {value: "n", label: "Pour 10000 habitants: "}, }, tip: {format:{x:false, y: false, annee: "d", n: d=> d.toLocaleString("fr-FR")}, fontSize: 12}}), //Plot.text(["↑ Nombre annuel de décès pour 10000 hbts*"], {x: 1922, y: 970, textAnchor: "start"}), Plot.arrow([1], {x:2021, y1:250, y2:100, bend:50}), Plot.text(["Epidémie\nCovid-19"], {x:2021, y:280, textAnchor: "end", fontSize:11}), Plot.ruleY([0]), Plot.ruleX([1925]) ] })33:T30e4,

	1950	1960	1970	1980	1990	2000	2010	2017	2018	2019	2020	2021	2022	2023(p)	2024(p)
Naissances (m)	862	820	850	800	762	775	802	770	759	753	735	742	726	678	663
Décès (m)	534	521	542	547	526	531	540	606	610	613	668	662	675	639	646
Excédent naturel (m)	328	299	308	253	236	244	262	163	149	140	66	80	51	39	17
Solde migratoire (m)	35	140	180	44	80	70	43	155	201	128	140	190	152	152	152
Variation totale (m)	363	439	488	297	316	314	305	318	349	268	206	270	203	191	169
Ajustement (2) (m)	-	-	-	-	-53	94	-	-100	-84	-84	49	93	-17	-	-

Taux de natalité (t)	20.6	17.9	16.7	14.9	13.4	13.1	12.8	11.5	11.3	11.2	10.9	10.9	10.7	9.9	9.7
Taux de mortalité (t)	12.8	11.4	10.7	10.2	9.3	9	8.6	9.1	9.1	9.1	9.9	9.7	9.9	9.4	9.4
Taux de mort. infantile (r)	52	27.4	18.2	10	7.3	4.4	3.5	3.9	3.8	3.8	3.6	3.7	3.9	4	4.1

Indice de fécondité (e)	2.95	2.74	2.48	1.94	1.78	1.87	2.02	1.89	1.87	1.86	1.82	1.83	1.78	1.66	1.62
Espérance de vie :
hommes (a)	63.4	67	68.4	70.2	72.7	75.3	78	79.4	79.5	79.7	79.1	79.2	79.3	79.9	80
femmes (a)	69.2	73.6	75.9	78.4	81	82.8	84.7	85.3	85.4	85.6	85.1	85.2	85.1	85.6	85.6

Mariages (3) (m)	331	320	394	334	287	298	245	234	235	225	156	219	242	242	247
Taux de nuptialité (t)	7.9	7	7.8	6.2	5.1	5	3.9	3.5	3.5	3.3	2.3	3.2	3.6	3.5	3.6

Population (4) (m)	42010	45904	51016	54029	56841	59267	63070	66992	67258	67442	67697	68060	68246	68437	68606
Moins de 20 ans (2) (m)	12710	14991	16772	16380	15605	15068	15440	16313	16287	16213	16119	16050	15960	15860	15734
65 ans ou plus (2) (m)	4796	5347	6598	7466	8039	9561	10667	13167	13462	13744	13967	14207	14422	14669	14925

Moins de 20 ans (2) %	30.3	32.7	32.9	30.3	27.5	25.4	24.5	24.4	24.2	24	23.8	23.6	23.4	23.2	22.9
65 ans ou plus (2) %	11.4	11.6	12.9	13.8	14.1	16.1	16.9	19.7	20	20.4	20.6	20.9	21.1	21.4	21.8

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\n Gilles Pison, Laurent Toulemon, Population & Sociétés, n° 631, mars 2025, Ined.
\nSources : Insee (observations) ; auteurs (projections).\n

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"caption1","database":"$undefined"},{"id":156,"value":"df2 = FileAttachment(\"n631_2@3.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":752,"value":"data2 = FileAttachment(\"n631_2b.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1229,"value":"heightLeg2 = {\nlet n;\n if (size>=700) {return n=200} \n if (size>=500) {return n=150}\n else {return n=120}\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1364,"value":"nticks = {\nlet n;\n if (size>500) {return n=10}\n else {return n =5}\n \n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":263,"value":"titre2 = html`Figure 2. Évolution de la population de la France d’ici 2070 selon différents scénarios`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":776,"value":"legend2 = Plot.plot({\n marginLeft: 0,\n marginTop: 0,\n marginBottom: 20,\n height:heightLeg2,\n width,\n y: {axis: false, domain: [2,4.5]},\n x: {domain: [0,4], axis: false}, \n marks: [\n\n Plot.ruleY([4], {x1: 0 , x2:.3, stroke: color[6], strokeWidth:strokeW, strokeDasharray: [3,6]}), \n Plot.text([\"Haut Insee 2021\"], {x:0.35, y: 4, textAnchor: \"start\", fontSize:12 }), \n\n Plot.ruleY([3.5], {x1: 0 , x2:.3, stroke: color[2], strokeWidth:strokeW}), \n Plot.text([\"2024 auteurs\"], {x:0.35, y: 3.5, textAnchor: \"start\", fontSize:12 }), \n \n Plot.ruleY([3], {x1: 0 , x2:.3, stroke: color[0], strokeWidth:strokeW}), \n Plot.text([\"Central Insee 2021\"], {x:0.35, y: 3, textAnchor: \"start\", fontSize:12 }), \n\n Plot.ruleY([2.5], {x1: 0 , x2:.3, stroke: color[7], strokeWidth:strokeW, strokeDasharray: [9,3]}), \n Plot.text([\"Bas Insee 2021\"], {x:0.35, y: 2.5, textAnchor: \"start\", fontSize:12 }), \n \n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":754,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":270,"value":"$30","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"caption2","database":"$undefined"},{"id":298,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":302,"value":"title3 = html`Figure 3. Évolution de l’espérance de vie à la naissance en France depuis 2000`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":304,"value":"df3 = FileAttachment(\"n631_3.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1311,"value":"legend3 = Plot.plot({marginTop:0, marginBottom:0, height: 1, color: {legend: true, domain: [\"Naissances\", \"Décès\"], range: [color[5], color[3]]}})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":306,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":688,"value":"

\nGilles Pison, Laurent Toulemon, Population & Sociétés, n° 631, mars 2025, Ined.
\nSource : Insee.\n \n

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"caption3","database":"$undefined"},{"id":331,"value":"### Figure 4","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":324,"value":"## Pyramide des âges\n\n* Dans un autre notebook, la css est trop spécifique. \n* ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1162,"value":"heightLeg3 = {\nlet n;\n if (size>=500) {return n=110}\n else {return n=70}\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":333,"value":"title5 = html`Figure 5. Évolution de la mortalité par causes de décès en France de 1925 à 2021`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":800,"value":"df5 = FileAttachment(\"n631_5b.csv\").csv({typed: true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":397,"value":"legend5 = Plot.plot({\n\n marginLeft: 0,\n marginTop: 5,\n marginBottom:20,\n height:heightLeg3,\n width,\n y: {axis: false, domain: [2.8,4.2]},\n x: {domain: [0,4], axis: false}, \n marks: [\n\nPlot.ruleY([4], {x1: 0 , x2:.25, stroke: color[4], strokeWidth:3}), \nPlot.text([\"Maladies infectueuses et respiratoires\"], {x:0.35, y: 4, textAnchor: \"start\", fontSize: 10}), \n\nPlot.ruleY([3.5], {x1: 0 , x2:.25, stroke: color[2], strokeDasharray: [4,4], strokeWidth:3}), \nPlot.text([\"Cancers\"], {x:0.35, y: 3.5, textAnchor: \"start\", fontSize: 10}), \n\nPlot.ruleY([3], {x1: 0 , x2:.25, stroke: color[0], strokeDasharray: [4,4], strokeWidth:3}), \nPlot.text([\"Maladies cardiovasculaires\"], {x:0.35, y: 3, textAnchor: \"start\", fontSize: 10}), \n \n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":803,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":685,"value":"

\nGilles Pison, Laurent Toulemon, Population & Sociétés, n° 631, mars 2025, Ined.
\nNote : * taux standardisés de mortalité, calculés à partir des taux par âge observés chaque année à une structure par âge fixe.
\nSources : Inserm-CepiDc, Breton et al. 2024 [4]\n \n

\n
","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"caption5","database":"$undefined"},{"id":1372,"value":"tabTitle = html `Tableau - Indicateurs démographiques de 1950 à 2024, France⁽¹⁾`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1374,"value":"$33","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"tabText","database":"$undefined"},{"id":1431,"value":"
\n(a) Années – (e) Nombre d’enfants par femme – (m) Milliers – (p) Provisoire – (r) Pour 1 000 naissances vivantes – (t) Pour 1 000 habitants.\t\t\t
\t\t\t\n(1) De 1950 à 2010 : France hexagonale ; à partir de 2017 : France entière (départements d’outre-mer inclus).\t\t\t\t\t\t\t\t\n(2) Les estimations de population pour les années 1990 et 2000 et les années 2017 à 2022 tiennent compte de divers ajustements destinés à rétablir la cohérence comptable\tentre les recensements de 1990, 1999 et 2006 (pour 1990 et 2000) et entre ceux des années 2017 et suivantes pour les années 2016 à 2022 [1].\t\t\t\n
\n(3) Y compris mariages de personnes de même sexe à partir de 2013.\t\t\n
\n(4) En fin d’année.\t\n
\nSource : Insee, Division des enquêtes et études démographiques (https://www.insee.fr).\t\t\n
\n
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