28:null 29:["$","title",null,{"children":"Tableau et graphique EN (node 3890) | Marc Thevenin | Observable"}] 2e:Tf25,

${df2.slice(0, 50).map(d => htl.html``)} ${filter.slice(0, 50).map(d => htl.html``)}

Countries	Number of residents 💬 Total population (thousands)	Number of births per 1,000 population 💬 Birth rate	Number of deaths per 1,000 population 💬 Mortality rate	Average length of life in years 💬 Life expectancy	Number of deaths of children aged under 1 per 1,000 births 💬 Infant mortality rate	Total fertility rate 💬 Number of children per woman	Share of people aged 65 and over 💬 % 65-years old and over	Annual increase, or decrease in number of residents, per 1,000 population (sum of migratory growth and natural increase) 💬 Growth rate
${d["Pays"]}	${d["Population_totale"].toLocaleString("en-US")}	${d["Taux_natalité"]}	${d["Taux_mortalité"]}	${d["Espérance_vie"]}	${d["Taux_mortalité_infantile"]}	${d["Nombre_enfant_femme"]}	${d["Part_65ans"]}	${d["Taux_croissance"]}
${d["Pays"]}	${d["Population_totale"]}	${d["Taux_natalité"]}	${d["Taux_mortalité"]}	${d["Espérance_vie"]}	${d["Taux_mortalité_infantile"]}	${d["Nombre_enfant_femme"]}	${d["Part_65ans"]}	${d["Taux_croissance"]}

2f:T153c,30:T718,plot = Plot.plot({ width: rWidth, height: Height, marginTop:0, marginLeft: rWidth>=600 ? 0.2*rWidth: 0.28*rWidth, marginRight: 30, x: {domain: [minX,max + 1], label: selectIndic, labelArrow: false, grid: true, ticks: nTicks}, y: {label: null, tickSize:0, padding:.4, inset: 10 }, caption: html`

`, marks: [ Plot.ruleX([0], {stroke: "black", strokeWidth: .5, strokeOpacity:1}), Plot.axisY({x: labyX, textAnchor: "end", dx:-5, lineWidth: width>400 ? 10 : 7}), Plot.barX(filterLong, {x: "valeur", y: "pays", stroke: d => selectReg2 === d.pays || d.pays===selectReg1 ? "black" : col, //fill: d => selectReg2 === d.pays || d.pays===selectReg1 ? color[0] : "#ff9a96", fill: col, strokeWidth: d=> width>500 ? 1 : 1, fillOpacity: d=> d.pays === selectReg1 || selectReg2 === d.pays ? 1 : .5, rx2: 0, rx1: 0, sort: {y: "x", reverse: true}, channels: { valeur: {value: "valeur", label: selectIndic }, pays: {value: "paysFEn", label: ""}, }, tip: {format: {pays: true, fillOpacity: false, strokeWidth: false, fill: false, z: false, y: false, valeur: d=> d.toLocaleString("en-US")}, stroke: "#222330"}, inset:1}), Plot.axisX({labelAnchor: "center", dy:10, marginBottom:mBottom, className: "xlabel", ticks: nTicks, tickFormat: d=> d.toLocaleString('en-US'), labelArrow: false}), Plot.ruleX([0], {stroke: "black", strokeWidth: 1}), ] })31:Ta7c,boxPlot = htl.html `

${viewof rWidth} ${display1}

Note for the reader: Note for the reader: The publication World Population Prospects provides United Nations population estimates for all countries in the world for each year from 1950 to 2023, as well as projections according to different scenarios (low, medium and high) for each year from 2024 to 2100. The figures presented here correspond to medium scenario projections for the given year.

Source: World Population Prospects. Nations Unies. 2024.

`32:T5c2,display1 = output=== "Table" ? html`

${viewof output} ${viewof selectReg1} ${viewof selectReg2}

${minimap}

${output2} ` : html`

${viewof output} ${viewof selectReg1} ${viewof selectReg2}

${viewof selectIndic}

${minimap}

${output2}

` 33:T458,dfLong = df2b.flatMap(d => [ { pays: d.Pays, paysFlag: d.PaysFlag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "Total population (thousands)", valeur: d.Population_totale}, { pays: d.Pays, paysFlag: d.paysFlag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "Birth rate", valeur: d.Taux_natalité}, { pays: d.Pays, paysFlag: d.paysFlag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "Mortality rate", valeur: d.Taux_mortalité}, { pays: d.Pays, paysFlag: d.paysFlag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "Life expectancy", valeur: d.Espérance_vie}, { pays: d.Pays, paysFlag: d.paysFlag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "Infant mortality rate", valeur: d.Taux_mortalité_infantile}, { pays: d.Pays, PaysFlag: d.PaysFlag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "Total fertility rate", valeur: d.Nombre_enfant_femme}, { pays: d.Pays, Paysflag: d.Paysflag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "Growth rate", valeur: d.Taux_croissance}, { pays: d.Pays, Paysflag: d.Paysflag, paysF: d.PaysF, paysFEn: d.PaysFEn, indic: "% 65-years old and over", valeur: d.Part_65ans}, 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et graphique EN (node 3890)","cells":[{"id":0,"value":"# Tableau et graphique EN (node 3890)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2704,"value":"yearCaption = new Date().getFullYear()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3424,"value":"//data = FileAttachment(\"paysMondeFinal@2.csv\").csv({typed:true}) ","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3526,"value":"data = FileAttachment(\"df(6).csv\").csv({typed:true})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":163,"value":"color = [\n \"#ff564e\", //rouge 0\n \"#ff7aad\", //rose 1\n \"#522673\", //mauve 2 \n \"#0042eb\", //bleu 3\n \"#5cd49e\", //vert 4\n \"#ffb322\", //jaune 5 \n \"#4f4f4f\", //gray 6\n \"#8a8a8a\", //gray light 7\n \"#0036bc\", //blue dark 8\n \"#ff362d\", // rouge dark 9\n \n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":258,"value":" data2 = data.map(d=>({\n Région1: d.Région1En,\n Région2: d.Région2En, \n Pays: d.paysEn,\n PaysF: d.paysf,\n PaysFEn : d.paysfEn,\n PaysFlag: d.Paysflag,\n Population_totale: d.Population_totale,\n Taux_natalité: d.Taux_natalité,\n Taux_mortalité: d.Taux_mortalité,\n Espérance_vie: d.Espérance_vie,\n Taux_mortalité_infantile: d.Taux_mortalité_infantile,\n Nombre_enfant_femme: d.Nombre_enfant_femme,\n Taux_croissance: d.Taux_croissance,\n Part_65ans: d.Part_65ans,\n }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":581,"value":"filter = data2.filter(d => d.Pays === selectReg2 && d.Région2!=\"--\" )","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":64,"value":"viewof selectReg1 = Inputs.select(reg1Array, {label: \"\", value: reg1Array})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":20,"value":"viewof selectReg2 = Inputs.select(reg2Array, {label: \"\", value: \"-\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":214,"value":" #### ${selectReg2} | Estimations 2024","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"titre","database":"$undefined"},{"id":123,"value":"$2e","pinned":true,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"tab","database":"$undefined"},{"id":2757,"value":"$2f","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"cssTab","database":"$undefined"},{"id":2858,"value":"viewof selectIndic = Inputs.select([\"Total population (thousands)\", \"Birth rate\", \"Mortality rate\", \"Life expectancy\", \"Infant mortality rate\", \"Total fertility rate\", \"Growth rate\", \"% 65-years old and over\" ], {label: \"\", value: \"Life 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\nSource : World Population Prospects. Nations Unies. 2024
\nNote de lecture: La publication World Population Prospects fournit les estimations de population des Nations Unies pour tous les pays du monde pour chaque année entre 1950 et 2023 et les projections selon différents scénarios (bas, moyen et haut) pour chaque année entre 2024 et 2100. Les chiffres présentés ici correspondent aux projections pour l’année en cours selon le scénario moyen. \n

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