2b:null 2c:["$","title",null,{"children":"Météo 2025-2026 France | Alain Ottenheimer | Observable"}] 31:T6c1,

[Météo-France](https://meteofrance.fr/) met à disposition, via la plateforme data.gouv.fr, des données climatologiques. Les données journalières de chaque département pour la période 2025-2026 sont regroupées dans une série de fichiers (un par département), mis à jour quotidiennement (avec un décalage de 3 jours) et disponibles dans plusieurs formats : CSV compressé (.csv.gz), GeoJSON, JSON et Parquet).
Consulter les jeux de données sur [data.gouv.fr](https://www.data.gouv.fr/datasets/donnees-climatologiques-de-base-quotidiennes?utm_source=chatgpt.com).
Le format ".parquet" présente un intérêt particulier, car il permet d’interroger le jeu de données à distance sans avoir à télécharger les fichiers au préalable.

Note méthodologique : Pour déterminer la liste des stations météo disponibles, il est nécessaire d’interroger chaque fichier afin d’en extraire les informations correspondantes. Comme cette opération n’a pas besoin d’être répétée systématiquement, elle est réalisée en amont à l’aide d’un script Python qui extrait, pour l’ensemble des stations, le numéro du département, le nom de la station ainsi que l’URL du fichier `.parquet`.
Le script est disponible dans l’onglet « Script Python » ci-dessous.

32:T19d1,chart_vent = { const FIXED_W = 650; const FIXED_H = 550; const container = document.createElement("div"); container.style.width = "100%"; function render(w) { // Use fixed size, shrink only if viewport is narrower const W = Math.min(FIXED_W, w); const H = Math.round((W / FIXED_W) * FIXED_H); const margin = Math.round(W * 0.1); const radius = Math.min(W * 0.75, H) / 2 - margin; const innerRadius = Math.max(15, Math.round(radius * 0.15)); const fontSize = Math.max(9, Math.round(W / 55)); const fontSizeTitle = Math.max(12, Math.round(W / 38)); const fontSizeSub = Math.max(10, Math.round(W / 48)); const min_date = new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(new Date(d3.min(data, (d) => d.date))); const max_date = new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(new Date(d3.max(data, (d) => d.date))); container.innerHTML = ""; const svg = d3.create("svg").attr("width", W).attr("height", H); svg .append("rect") .attr("width", W) .attr("height", H) .attr("fill", "#F5F5F5") .attr("rx", 8) .attr("ry", 8); svg .append("rect") .attr("width", W - 2) .attr("height", H - 2) .attr("x", 1) .attr("y", 1) .attr("fill", "none") .attr("stroke", "#cccccc") .attr("stroke-width", 1.5) .attr("rx", 8) .attr("ry", 8); const g = svg .append("g") .attr("transform", `translate(${W * 0.42}, ${H * 0.58})`); const speed_labels = ["<2", "2-4", "4-6", "6-8", "8-10", ">10"]; const dir_labels = [ "N", "NNE", "NE", "ENE", "E", "ESE", "SE", "SSE", "S", "SSW", "SW", "WSW", "W", "WNW", "NW", "NNW" ]; const totals = dir_labels.map((dir) => d3.sum( speed_labels, (spd) => data_vent.files[0].data.find( (d) => d.Angle === dir && d.Speed === spd )?.Hours ?? 0 ) ); const maxTotal = d3.max(totals); const rScale = d3 .scaleLinear() .domain([0, maxTotal]) .range([innerRadius, radius]); const color = d3 .scaleOrdinal() .domain(speed_labels) .range([ "#eff3ff", "#c6dbef", "#9ecae1", "#6baed6", "#3182bd", "#08519c" ]); const angleStep = (2 * Math.PI) / dir_labels.length; dir_labels.forEach((dir, i) => { const angle_rad = i * angleStep; let bottom = 0; speed_labels.forEach((spd) => { const row = data_vent.files[0].data.find( (d) => d.Angle === dir && d.Speed === spd ); const value = row?.Hours ?? 0; if (value === 0) { bottom += value; return; } const arc = d3 .arc() .innerRadius(rScale(bottom)) .outerRadius(rScale(bottom + value)) .startAngle(angle_rad - angleStep / 2) .endAngle(angle_rad + angleStep / 2); g.append("path") .attr("d", arc) .attr("fill", color(spd)) .attr("opacity", 0.85) .append("title") .text(`${dir} · ${spd} m/s: ${value.toFixed(2)}%`); bottom += value; }); }); rScale.ticks(4).forEach((t) => { g.append("circle") .attr("r", rScale(t)) .attr("fill", "none") .attr("stroke", "#ccc") .attr("stroke-dasharray", "3,3"); g.append("text") .attr("x", 4) .attr("y", -rScale(t)) .attr("font-size", fontSize) .attr("fill", "#777") .text(`${t.toFixed(0)}%`); }); dir_labels.forEach((_, i) => { const a = i * angleStep; g.append("line") .attr("x1", innerRadius * Math.sin(a)) .attr("y1", -innerRadius * Math.cos(a)) .attr("x2", radius * Math.sin(a)) .attr("y2", -radius * Math.cos(a)) .attr("stroke", "#999") .attr("stroke-width", 1) .attr("stroke-dasharray", "3,3"); }); dir_labels.forEach((dir, i) => { const a = i * angleStep; const labelR = radius + fontSize + 4; g.append("text") .attr("x", labelR * Math.sin(a)) .attr("y", -labelR * Math.cos(a)) .attr("text-anchor", "middle") .attr("dominant-baseline", "middle") .attr("font-family", "var(--sans-serif, system-ui, sans-serif)") .attr("font-size", fontSize + 1) .attr("font-weight", dir.length <= 1 ? "bold" : "normal") .text(dir); }); const title = svg .append("text") .attr("x", W * 0.42) .attr("y", 22) .attr("text-anchor", "middle"); title .append("tspan") .attr("x", W * 0.42) .attr("dy", "0em") .attr("font-size", fontSizeTitle) .attr("font-weight", "500") .attr("font-family", "var(--sans-serif, system-ui, sans-serif)") .attr("fill", "currentColor") .text(`Rose des vents - Station ${name.split(" -")[0]}`); title .append("tspan") .attr("x", W * 0.42) .attr("dy", "1.6em") .attr("font-size", fontSizeSub) .attr("font-weight", "400") .attr("font-family", "var(--sans-serif, system-ui, sans-serif)") .attr("fill", "#707070") .text(`entre le ${min_date} et le ${max_date}`); const legend = svg .append("g") .attr("transform", `translate(${W * 0.86}, ${H * 0.15})`); legend .append("text") .attr("font-size", fontSize + 1) .attr("font-weight", "600") .attr("font-family", "var(--sans-serif, system-ui, sans-serif)") .text("Vitesse (m/s)"); speed_labels.forEach((spd, i) => { const row = legend .append("g") .attr("transform", `translate(0, ${i * (fontSize + 7) + 16})`); row .append("rect") .attr("width", fontSize) .attr("height", fontSize) .attr("fill", color(spd)); row .append("text") .attr("x", fontSize + 5) .attr("y", fontSize - 1) .attr("font-size", fontSize) .attr("font-family", "var(--sans-serif, system-ui, sans-serif)") .text(spd); }); container.appendChild(svg.node()); } render(width); const ro = new ResizeObserver((entries) => { const w = Math.floor(entries[0].contentRect.width); if (w > 0) render(w); }); ro.observe(container); invalidation.then(() => ro.disconnect()); return container; }33:T807,data = { // 1️⃣ Column names const speed_col = "FXY"; const dir_col = "DXY"; // 2️⃣ Convert wind speed (replace comma decimal separator, parse float) const A_filter = temp2.map((d) => ({ ...d, [speed_col]: parseFloat(String(d[speed_col]).replace(",", ".")) })); // 3️⃣ Convert wind direction to numeric, normalize 360° → 0° A_filter.forEach((d) => { const v = parseFloat(d[dir_col]); d[dir_col] = isNaN(v) ? null : ((v % 360) + 360) % 360; }); // 4️⃣ Direction sectors const dir_labels = [ "N", "NNE", "NE", "ENE", "E", "ESE", "SE", "SSE", "S", "SSW", "SW", "WSW", "W", "WNW", "NW", "NNW" ]; A_filter.forEach((d) => { if (d[dir_col] == null) { d.dir_grp = null; } else { const idx = Math.floor((d[dir_col] + 11.25) / 22.5) % 16; d.dir_grp = dir_labels[idx]; } }); // 5️⃣ Speed classes const speed_bins = [0, 2, 4, 6, 8, 10, Infinity]; const speed_labels = ["<2", "2-4", "4-6", "6-8", "8-10", ">10"]; function speedGroup(v) { if (isNaN(v) || v == null) return null; for (let i = 0; i < speed_bins.length - 1; i++) { if (v >= speed_bins[i] && v < speed_bins[i + 1]) return speed_labels[i]; } return null; } A_filter.forEach((d) => { d.speed_grp = speedGroup(d[speed_col]); }); // 6️⃣ Frequency table (counts → %) // Initialize full matrix with zeros const freq = {}; for (const dir of dir_labels) { freq[dir] = {}; for (const spd of speed_labels) freq[dir][spd] = 0; } // Count let total = 0; for (const d of A_filter) { if (d.dir_grp && d.speed_grp) { freq[d.dir_grp][d.speed_grp]++; total++; } } // Convert to % for (const dir of dir_labels) for (const spd of speed_labels) freq[dir][spd] = total > 0 ? (freq[dir][spd] / total) * 100 : 0; // 7️⃣ Angles (radians), one per sector const angles = dir_labels.map((_, i) => (i * 22.5 * Math.PI) / 180); return A_filter; }34:T8d8,data_vent = { // 1️⃣ Column names const speed_col = "FXY"; const dir_col = "DXY"; // 2️⃣ Convert wind speed const A_filter = temp2.map((d) => ({ ...d, [speed_col]: parseFloat(String(d[speed_col]).replace(",", ".")) })); // 3️⃣ Convert wind direction to numeric, normalize 360° → 0° A_filter.forEach((d) => { const v = parseFloat(d[dir_col]); d[dir_col] = isNaN(v) ? null : ((v % 360) + 360) % 360; }); // 4️⃣ Direction sectors const dir_labels = [ "N", "NNE", "NE", "ENE", "E", "ESE", "SE", "SSE", "S", "SSW", "SW", "WSW", "W", "WNW", "NW", "NNW" ]; A_filter.forEach((d) => { if (d[dir_col] == null) { d.dir_grp = null; } else { const idx = Math.floor((d[dir_col] + 11.25) / 22.5) % 16; d.dir_grp = dir_labels[idx]; } }); // 5️⃣ Speed classes const speed_bins = [0, 2, 4, 6, 8, 10, Infinity]; const speed_labels = ["<2", "2-4", "4-6", "6-8", "8-10", ">10"]; function speedGroup(v) { if (isNaN(v) || v == null) return null; for (let i = 0; i < speed_bins.length - 1; i++) { if (v >= speed_bins[i] && v < speed_bins[i + 1]) return speed_labels[i]; } return null; } A_filter.forEach((d) => { d.speed_grp = speedGroup(d[speed_col]); }); // 6️⃣ Frequency table (counts → %) const freq = {}; for (const dir of dir_labels) { freq[dir] = {}; for (const spd of speed_labels) freq[dir][spd] = 0; } let total = 0; for (const d of A_filter) { if (d.dir_grp && d.speed_grp) { freq[d.dir_grp][d.speed_grp]++; total++; } } for (const dir of dir_labels) for (const spd of speed_labels) freq[dir][spd] = total > 0 ? (freq[dir][spd] / total) * 100 : 0; // 7️⃣ Angles (radians), one per sector const angles = dir_labels.map((_, i) => (i * 22.5 * Math.PI) / 180); // 8️⃣ Return everything return { name: name, files: [ { name: name, data: dir_labels.flatMap((dir, i) => speed_labels.map((spd) => ({ Angle: dir, Speed: spd, Hours: freq[dir][spd], angle_rad: angles[i] })) ) } ] }; }35:T7d4,{ // 1️⃣ Column names const speed_col = "FXY"; const dir_col = "DXY"; // 2️⃣ Convert wind speed const A_filter = temp2.map((d) => ({ ...d, [speed_col]: parseFloat(String(d[speed_col]).replace(",", ".")) })); // 3️⃣ Convert wind direction to numeric, normalize 360° → 0° A_filter.forEach((d) => { const v = parseFloat(d[dir_col]); d[dir_col] = isNaN(v) ? null : ((v % 360) + 360) % 360; }); // 4️⃣ Direction sectors const dir_labels = [ "N", "NNE", "NE", "ENE", "E", "ESE", "SE", "SSE", "S", "SSW", "SW", "WSW", "W", "WNW", "NW", "NNW" ]; A_filter.forEach((d) => { if (d[dir_col] == null) { d.dir_grp = null; } else { const idx = Math.floor((d[dir_col] + 11.25) / 22.5) % 16; d.dir_grp = dir_labels[idx]; } }); // 5️⃣ Speed classes const speed_bins = [0, 2, 4, 6, 8, 10, Infinity]; const speed_labels = ["<2", "2-4", "4-6", "6-8", "8-10", ">10"]; function speedGroup(v) { if (isNaN(v) || v == null) return null; for (let i = 0; i < speed_bins.length - 1; i++) { if (v >= speed_bins[i] && v < speed_bins[i + 1]) return speed_labels[i]; } return null; } A_filter.forEach((d) => { d.speed_grp = speedGroup(d[speed_col]); }); // 6️⃣ Frequency table (counts → %) const freq = {}; for (const dir of dir_labels) { freq[dir] = {}; for (const spd of speed_labels) freq[dir][spd] = 0; } let total = 0; for (const d of A_filter) { if (d.dir_grp && d.speed_grp) { freq[d.dir_grp][d.speed_grp]++; total++; } } for (const dir of dir_labels) for (const spd of speed_labels) freq[dir][spd] = total > 0 ? (freq[dir][spd] / total) * 100 : 0; // 7️⃣ Angles (radians), one per sector const angles = dir_labels.map((_, i) => (i * 22.5 * Math.PI) / 180); // 8️⃣ Return everything return { A_filter, freq, dir_labels, speed_labels, angles }; }36:T12e3,function createTempPlot(data, variable, var_name) { const k = 1; const n = 10; const yMax = variable + "X"; const yMin = variable + "N"; const minDate = d3.min(data, (d) => d.date); const maxDate = d3.max(data, (d) => d.date); const diffDays = (maxDate - minDate) / (1000 * 60 * 60 * 24); const shortRange = diffDays < 60; const min_date = new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(new Date(minDate)); const max_date = new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(new Date(maxDate)); return Plot.plot({ clip: false, height: 400, width: 650, marginRight: 50, marginLeft: 50, marginBottom: 60, marginTop: 65, style: { background: "#F5F5F5", color: "#000", fontSize: "11px" }, x: { type: "time", label: null, grid: true, domain: [minDate, maxDate], // Ticks quotidiens si < 60j, sinon mensuels ticks: shortRange ? d3.timeDay.every(1) : d3.timeMonth.every(1), // Label tous les 7 jours (lundi) si < 60j, sinon format mois/année tickFormat: shortRange ? (d) => (d.getDay() === 1 ? frLocale.format("%d %b")(d) : "") : frLocale.format("%b %Y"), tickRotate: -25, nice: false }, y: { grid: true, //label: "Température (°C)", domain: [-20, 50], ticks: 10, tickFormat: d3.format(".0f") }, marks: [ Plot.frame(), // ____________________________Left y-axis Plot.axisY({ anchor: "left", label: null, labelAnchor: "center", ticks: 10, tickFormat: d3.format(".0f") }), // __________________________Right y-axis Plot.axisY({ anchor: "right", label: null, labelAnchor: "center", ticks: 10, tickFormat: d3.format(".0f") }), // ___________________________Tmax line Plot.lineY(data, { x: "date", y: yMax, strokeWidth: 2, stroke: "red", tip: { format: { x: (d) => d.toLocaleDateString("fr-FR", { day: "numeric", month: "long", year: "numeric" }), y: true, stroke: false } } }), //_____________________________Tmin line Plot.lineY(data, { x: "date", y: yMin, strokeWidth: 2, stroke: "#009fff", tip: { format: { y: true, x: false, stroke: false } } }), //__________________________________Vertical line end of year ...(periode === "2025-2026" ? [ Plot.ruleX([new Date("2026-01-01")], { y1: -20, y2: 50, stroke: "black", strokeWidth: 1, strokeDasharray: "4,4" }) ] : []), // ________________________________Label axe Y gauche (horizontal) Plot.text([data[0]], { text: ["Température (°C)"], frameAnchor: "top-left", fontSize: 11, fill: "#555", textAnchor: "start", dx: -45, dy: -19 }), //_________________________________Label axe Y droit (horizontal) Plot.text([data[0]], { text: ["Température (°C)"], frameAnchor: "top-right", fontSize: 11, fill: "#555", textAnchor: "end", dx: 45, dy: -19 }), // ___________________________________Station label Plot.text([data[0]], { text: (d) => "Station de " + d.NOM_USUEL, frameAnchor: "top-right", fillOpacity: 1, fontSize: 14, fontWeight: "500", fill: "black", textAnchor: "end", dx: 45, dy: -60 }), // __________________________________________________ titre Plot.text([data[0]], { text: [`T° ${var_name}`], frameAnchor: "top-left", fontSize: 15, fontWeight: "600", fill: "black", dx: -45, dy: -60 }), // __________________________________________________ Sous-titre Plot.text([data[0]], { text: [`en °C entre le ${min_date} et le ${max_date}`], frameAnchor: "top-left", fontSize: 13, fontWeight: "400", fill: "#444", dx: -45, dy: -43 }), // __________________________________________________ Caption Plot.text([data[0]], { text: [`Source : data.gouv`], frameAnchor: "bottom-left", fontSize: 12, fill: "#888", dx: -45, dy: +40 }) ] }); }37:T15ca,function createTempPlotLisse(data, variable, var_name) { const k = 1; const n = 10; const yMax = variable + "X"; const yMin = variable + "N"; const min_date = new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(new Date(d3.min(data, (d) => d.date))); const max_date = new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(new Date(d3.max(data, (d) => d.date))); return Plot.plot({ clip: false, height: 400, width: 650, marginRight: 50, marginLeft: 50, marginBottom: 60, marginTop: 65, style: { background: "#F5F5F5", color: "#000", fontSize: "11px" }, x: { type: "time", label: null, grid: true, domain: [d3.min(data, (d) => d.date), d3.max(data, (d) => d.date)], ticks: d3.timeMonth.every(1), tickFormat: frLocale.format("%b %Y"), tickRotate: -25, nice: false }, y: { grid: true, label: null, domain: [-20, 50], ticks: 10, tickFormat: d3.format(".0f") }, marks: [ //Plot.ruleY([0]), Plot.frame(), // __________________________________________________ Tmax bollinger Plot.lineY( data, Plot.mapY(Plot.bollinger({ n: n, k: k, anchor: "middle" }), { x: "date", y: yMax, strokeWidth: 3, stroke: "red", channels: { tmax: "TX", tmin: "TN" } /*tip: { format: { y: false, x: (d) => d.toLocaleDateString("fr-FR", { day: "numeric", month: "long", year: "numeric" }), stroke: false } }*/ }) ), // __________________________________________________ Tmax line Plot.lineY(data, { x: "date", y: yMax, stroke: "red", strokeWidth: 0.5, tip: { format: { x: (d) => d.toLocaleDateString("fr-FR", { day: "numeric", month: "long", year: "numeric" }), y: true, stroke: false } } }), // ________________________________________________ Tmin bollinger Plot.lineY( data, Plot.mapY(Plot.bollinger({ n: n, k: -k, anchor: "middle" }), { x: "date", y: yMin, strokeWidth: 3, stroke: "#009fff" }) ), // __________________________________________________ Tmin line Plot.lineY(data, { x: "date", y: yMin, strokeWidth: 0.5, stroke: "#009fff", tip: { format: { x: false, y: true, stroke: false } } }), // _____________________________________________ vertical line end of year (() => { if (periode === "2025-2026") { return Plot.ruleX([new Date("2026-01-01")], { y1: -20, y2: 50, stroke: "black", strokeWidth: 1, strokeDasharray: "4,4" }); } })(), // ______________________________________________ Left y-axis Plot.axisY({ anchor: "left", label: null, labelAnchor: "center", ticks: 10, tickFormat: d3.format(".0f") }), // ______________________________________________ Right y-axis Plot.axisY({ anchor: "right", label: null, labelAnchor: "center", ticks: 10, tickFormat: d3.format(".0f") }), // ____________________________________ Label axe Y gauche (horizontal) Plot.text([data[0]], { text: ["Température (°C)"], frameAnchor: "top-left", fontSize: 11, fill: "#555", textAnchor: "start", dx: -45, dy: -19 }), // ________________________________________Label axe Y droit (horizontal) Plot.text([data[0]], { text: ["Température (°C)"], frameAnchor: "top-right", fontSize: 11, fill: "#555", textAnchor: "end", dx: 45, dy: -19 }), // ____________________________________________Station label Plot.text([data[0]], { text: (d) => "Station de " + d.NOM_USUEL, frameAnchor: "top-right", fillOpacity: 1, fontSize: 14, fontWeight: "500", fill: "black", textAnchor: "end", dx: 45, dy: -60 }), // __________________________________________________ titre Plot.text([data[0]], { text: [`T° ${var_name}`], frameAnchor: "top-left", fontSize: 15, fontWeight: "600", fill: "black", dx: -45, dy: -60 }), // __________________________________________________ Sous-titre Plot.text([data[0]], { text: [`en °C entre le ${min_date} et le ${max_date}`], frameAnchor: "top-left", fontSize: 13, fontWeight: "400", fill: "#444", dx: -45, dy: -43 }), // __________________________________________________ Caption Plot.text([data[0]], { text: [`Source : data.gouv`], frameAnchor: "bottom-left", fontSize: 12, fill: "#888", dx: -45, dy: +53 }) ] }); }38:T1bd9,function createRainPlot(data, var_name, title) { // ── Aggregate by week or month depending on x-domain span ───────────────── const xMin = d3.min(data, (d) => d.date); const xMax = d3.max(data, (d) => d.date); const spanMonths = d3.timeMonth.count(xMin, xMax); const useWeekly = spanMonths < 5; const groupedData = Array.from( d3.rollup( data, (v) => d3.sum(v, (d) => d.RR), (d) => useWeekly ? d3.timeMonday.floor(d.date) : d3.timeMonth.floor(d.date) ), ([period, totalRR]) => ({ period, totalRR }) ).sort((a, b) => a.period - b.period); const periodEnd = (d) => useWeekly ? d3.timeMonday.offset(d.period, 1) : d3.timeMonth.offset(d.period, 1); // ── Midpoint of each bar (used for ticks + text labels) ─────────────────── const midpoint = (d) => new Date((d.period.getTime() + periodEnd(d).getTime()) / 2); const max_val = d3.max(groupedData, (d) => d.totalRR); const yMax = max_val < 150 ? 200 : max_val * 1.1; const total = d3.sum(groupedData, (d) => d.totalRR); // ── Extend x domain by half a period on each side ───────────────────────── const halfPeriodMs = useWeekly ? 3.5 * 24 * 60 * 60 * 1000 : 15 * 24 * 60 * 60 * 1000; const xDomainMin = new Date(xMin.getTime() - halfPeriodMs); const xDomainMax = new Date(xMax.getTime() + halfPeriodMs); // ── Ticks at bar midpoints ───────────────────────────────────────────────── //const tickValues = groupedData.map(midpoint); // ── Ticks at bar midpoints ───────────────────────────────────────────────── const tickValues = groupedData.map(midpoint); const tooManyTicks = tickValues.length > 12; const tickFmt = useWeekly ? (d) => { const idx = tickValues.findIndex((t) => t.getTime() === d.getTime()); if (tooManyTicks && idx % 2 !== 0) return ""; const bar = groupedData[idx]; if (!bar) return ""; const wn = isoWeek(bar.period); const label = bar.period.toLocaleDateString("fr-FR", { day: "numeric", month: "short" }) + "→ "; return `S${wn}\n${label}`; } : (d) => { const idx = tickValues.findIndex((t) => t.getTime() === d.getTime()); if (tooManyTicks && idx % 2 !== 0) return ""; const bar = groupedData[idx]; if (!bar) return ""; return bar.period.toLocaleDateString("fr-FR", { month: "short", year: "numeric" }); }; // Week number helper (ISO) const isoWeek = (date) => { const d = new Date(date); d.setHours(0, 0, 0, 0); d.setDate(d.getDate() + 4 - (d.getDay() || 7)); const yearStart = new Date(d.getFullYear(), 0, 1); return Math.ceil(((d - yearStart) / 86400000 + 1) / 7); }; const gapMs = useWeekly ? 0.4 * 24 * 60 * 60 * 1000 : 1.5 * 24 * 60 * 60 * 1000; const fmtDate = (d) => new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(d); const plot = Plot.plot({ height: 400, width: 650, marginRight: 50, marginLeft: 50, marginBottom: 60, marginTop: 65, style: { background: "#F5F5F5", color: "#000", fontSize: "11px", overflow: "visible" }, x: { type: "time", label: null, grid: true, domain: [xDomainMin, xDomainMax], ticks: tickValues, // ← midpoints only, no auto ticks tickFormat: tickFmt, tickRotate: useWeekly ? -35 : -25, nice: false }, y: { grid: true, label: null, domain: [0, yMax], tickFormat: d3.format(".0f") }, marks: [ Plot.frame(), Plot.rectY(groupedData, { x1: (d) => new Date(d.period.getTime() + gapMs), x2: (d) => new Date(periodEnd(d).getTime() - gapMs), y1: 0, y2: (d) => d.totalRR, fill: "#2196F3", fillOpacity: 0.75, stroke: "#2196F3", strokeWidth: 0.5, tip: { format: { x1: null, x2: null, y1: null, y2: (d) => d3.format(".1f")(d) + " mm" } } }), //____________________________ Value labels at bar midpoints Plot.text(groupedData, { x: midpoint, y: (d) => d.totalRR, text: (d) => d3.format(".0f")(d.totalRR), dy: -8, fontSize: 13, fill: "#333", textAnchor: "middle" }), //_______________________________ Total — top right Plot.text([{}], { x: xDomainMax, y: yMax, text: [`Total sur la période = ${d3.format(".0f")(total)} mm`], textAnchor: "end", fontSize: 15, fontWeight: "bold", fill: "#333", dy: 10, dx: -4 }), ...(periode === "2025-2026" ? [ Plot.ruleX([new Date("2026-01-01")], { y1: 0, y2: yMax, stroke: "black", strokeWidth: 1, strokeDasharray: "4,4" }) ] : []), // ________________________________Label axe Y (horizontal) Plot.text([data[0]], { text: [`mm / ${useWeekly ? "sem." : "mois"}`], frameAnchor: "top-left", fontSize: 10, fill: "#555", textAnchor: "start", dx: -45, dy: -19 }), // __________________________________Station label Plot.text([data[0]], { text: (d) => "Station de " + d.NOM_USUEL, frameAnchor: "top-right", fillOpacity: 1, fontSize: 14, fontWeight: "500", fill: "black", textAnchor: "end", dx: 45, dy: -60 }), // __________________________________________ titre Plot.text([data[0]], { text: [ `Précipitations ${ useWeekly ? "hebdomadaires" : "mensuelles" } cumulées` ], frameAnchor: "top-left", fontSize: 15, fontWeight: "600", fill: "black", dx: -45, dy: -60 }), // __________________________________________________ Sous-titre Plot.text([data[0]], { text: [`en mm entre le ${fmtDate(xMin)} et le ${fmtDate(xMax)}`], frameAnchor: "top-left", fontSize: 13, fontWeight: "400", fill: "#444", dx: -45, dy: -43 }), // __________________________________________________ Caption Plot.text([data[0]], { text: [`Source : data.gouv`], frameAnchor: "bottom-left", fontSize: 12, fill: "#888", dx: -45, dy: +56 }) ] }); const container = document.createElement("div"); container.appendChild(plot); return container; }39:T1ef5,function createDurationPlot(data, var_name, title) { // ── Aggregate by week or month depending on x-domain span ───────────────── const xMin = d3.min(data, (d) => d.date); const xMax = d3.max(data, (d) => d.date); const spanMonths = d3.timeMonth.count(xMin, xMax); const useWeekly = spanMonths < 5; const groupedData = Array.from( d3.rollup( data, (v) => d3.sum(v, (d) => d.DRR), // ← DRR instead of RR (d) => useWeekly ? d3.timeMonday.floor(d.date) : d3.timeMonth.floor(d.date) ), ([period, totalDRR]) => ({ period, totalDRR }) ).sort((a, b) => a.period - b.period); const periodEnd = (d) => useWeekly ? d3.timeMonday.offset(d.period, 1) : d3.timeMonth.offset(d.period, 1); const midpoint = (d) => new Date((d.period.getTime() + periodEnd(d).getTime()) / 2); const max_val_h = d3.max(groupedData, (d) => d.totalDRR) / 60; // max bar in hours const yMax = (max_val_h < 50 ? 70 : max_val_h * 1.2) * 60; const total = d3.sum(groupedData, (d) => d.totalDRR); // ── Extend x domain by half a period on each side ───────────────────────── const halfPeriodMs = useWeekly ? 3.5 * 24 * 60 * 60 * 1000 : 15 * 24 * 60 * 60 * 1000; const xDomainMin = new Date(xMin.getTime() - halfPeriodMs); const xDomainMax = new Date(xMax.getTime() + halfPeriodMs); // ── Ticks at bar midpoints ───────────────────────────────────────────────── const tickValues = groupedData.map(midpoint); const tooManyTicks = tickValues.length > 12; // Week number helper (ISO) const isoWeek = (date) => { const d = new Date(date); d.setHours(0, 0, 0, 0); d.setDate(d.getDate() + 4 - (d.getDay() || 7)); const yearStart = new Date(d.getFullYear(), 0, 1); return Math.ceil(((d - yearStart) / 86400000 + 1) / 7); }; const tickFmt = useWeekly ? (d) => { const idx = tickValues.findIndex((t) => t.getTime() === d.getTime()); if (tooManyTicks && idx % 2 !== 0) return ""; const bar = groupedData[idx]; if (!bar) return ""; const wn = isoWeek(bar.period); const label = bar.period.toLocaleDateString("fr-FR", { day: "numeric", month: "short" }) + "→ "; return `S${wn}\n${label}`; } : (d) => { const idx = tickValues.findIndex((t) => t.getTime() === d.getTime()); if (tooManyTicks && idx % 2 !== 0) return ""; const bar = groupedData[idx]; if (!bar) return ""; return bar.period.toLocaleDateString("fr-FR", { month: "short", year: "numeric" }); }; const gapMs = useWeekly ? 0.4 * 24 * 60 * 60 * 1000 : 1.5 * 24 * 60 * 60 * 1000; const fmtDate = (d) => new Intl.DateTimeFormat("fr-FR", { day: "numeric", month: "long", year: "numeric" }).format(d); // ── Duration formatter: converts minutes → "Xh YYmin" ──────────────────── const fmtDuration = (minutes) => { const h = Math.floor(minutes / 60); const m = Math.round(minutes % 60); if (h === 0) return `${m}min`; if (m === 0) return `${h}h`; return `${h}h${String(m).padStart(2, "0")}`; }; const fmtTotal = (minutes) => { const days = Math.floor(minutes / (60 * 24)); const h = Math.floor((minutes % (60 * 24)) / 60); if (days === 0) return `${h}h`; if (h === 0) return `${days}j`; return `${days}j ${h}h`; }; const plot = Plot.plot({ //title: `${title} `, //subtitle: `en heures entre le ${fmtDate(xMin)} et le ${fmtDate(xMax)}`, //caption: "Source : data.gouv", height: 400, width: 650, marginRight: 50, marginLeft: 50, marginBottom: 60, marginTop: 65, style: { background: "#F5F5F5", color: "#000", fontSize: "11px", overflow: "visible" }, x: { type: "time", label: null, grid: true, domain: [xDomainMin, xDomainMax], ticks: tickValues, tickFormat: tickFmt, tickRotate: useWeekly ? -35 : -25, nice: false }, y: { grid: true, //label: "h / " + (useWeekly ? "sem." : "mois"), domain: [0, yMax], tickFormat: (d) => `${Math.round(d / 60)}h`, ticks: d3.range(0, yMax + 1, 600) // 600 min = 10h }, marks: [ Plot.frame(), Plot.rectY(groupedData, { x1: (d) => new Date(d.period.getTime() + gapMs), x2: (d) => new Date(periodEnd(d).getTime() - gapMs), y1: 0, y2: (d) => d.totalDRR, fill: "#ff7f00", // ← distinct green-teal for duration fillOpacity: 0.75, stroke: "#ff7f00", strokeWidth: 0.5, tip: { format: { x1: null, x2: null, y1: null, y2: (d) => fmtDuration(d) // ← tip shows "Xh YYmin" } } }), // Value labels at bar midpoints Plot.text(groupedData, { x: midpoint, y: (d) => d.totalDRR, text: (d) => fmtDuration(d.totalDRR), dy: -8, fontSize: 10, fill: "#333", textAnchor: "middle" }), // Total — top right Plot.text([{}], { x: xDomainMax, y: yMax, // total top right text: [`Total sur la période = ${fmtTotal(total)}`], textAnchor: "end", fontSize: 15, fontWeight: "bold", fill: "#333", dy: 10, dx: -4 }), ...(periode === "2025-2026" ? [ Plot.ruleX([new Date("2026-01-01")], { y1: 0, y2: yMax, stroke: "black", strokeWidth: 1, strokeDasharray: "4,4" }) ] : []), // ── Label axe Y (horizontal) ─────────────────────────────────────── Plot.text([data[0]], { text: [`mm / ${useWeekly ? "sem." : "mois"}`], frameAnchor: "top-left", fontSize: 10, fill: "#555", textAnchor: "start", dx: -45, dy: -19 }), // ── Station label ────────────────────────────────────────────────────── Plot.text([data[0]], { text: (d) => "Station de " + d.NOM_USUEL, frameAnchor: "top-right", fillOpacity: 1, fontSize: 14, fontWeight: "500", fill: "black", textAnchor: "end", dx: 45, dy: -60 }), // __________________________________________________ titre Plot.text([data[0]], { text: [ `Durées de précipitation ${ useWeekly ? "hebdomadaires" : "mensuelles" } cumulées` ], frameAnchor: "top-left", fontSize: 15, fontWeight: "600", fill: "black", dx: -45, dy: -60 }), // __________________________________________________ Sous-titre Plot.text([data[0]], { text: [`en mm entre le ${fmtDate(xMin)} et le ${fmtDate(xMax)}`], frameAnchor: "top-left", fontSize: 13, fontWeight: "400", fill: "#444", dx: -45, dy: -43 }), // __________________________________________________ Caption Plot.text([data[0]], { text: [`Source : data.gouv`], frameAnchor: "bottom-left", fontSize: 12, fill: "#888", dx: -45, dy: +56 }) ] }); const container = document.createElement("div"); container.appendChild(plot); return container; }3a:Tdbd,note1 = md`# MySQL Key Commands Reference ## 1. Data Request Commands (\`SELECT\` & Clauses) These commands and clauses are the core of MySQL requests. They are used to query, filter, sort, and fetch data from your database. | Command / Clause | Description | Basic Syntax Example | | :--- | :--- | :--- | | **\`SELECT\`** | Retrieves data from one or more tables. Use \`*\` to fetch all columns. | \`SELECT column1, column2 FROM table_name;\` | | **\`WHERE\`** | Filters records based on specific conditions. | \`SELECT * FROM users WHERE age >= 18;\` | | **\`AND\` / \`OR\` / \`NOT\`** | Combines multiple filtering conditions inside a \`WHERE\` clause. | \`SELECT * FROM products WHERE price < 50 AND stock > 0;\` | | **\`ORDER BY\`** | Sorts the result-set in ascending (\`ASC\`, default) or descending (\`DESC\`) order. | \`SELECT * FROM employees ORDER BY salary DESC;\` | | **\`LIMIT\`** | Specifies the maximum number of records to return (great for pagination). | \`SELECT * FROM articles LIMIT 10;\` | | **\`LIKE\`** | Searches for a pattern using wildcards (\`%\` for multiple characters, \`_\` for one). | \`SELECT * FROM clients WHERE name LIKE 'John%';\` | | **\`IN\`** | Specifies multiple possible values for a single column. | \`SELECT * FROM orders WHERE status IN ('shipped', 'delivered');\` | | **\`BETWEEN\`** | Filters data within an inclusive range (numbers, text, or dates). | \`SELECT * FROM sales WHERE date BETWEEN '2026-01-01' AND '2026-03-31';\` | | **\`GROUP BY\`** | Groups rows that have the same values into summary rows (used with aggregate functions like \`COUNT\`, \`SUM\`, \`AVG\`). | \`SELECT department, COUNT(*) FROM staff GROUP BY department;\` | | **\`HAVING\`** | Filters grouped data. Works exactly like \`WHERE\`, but specifically for \`GROUP BY\` aggregations. | \`SELECT country, COUNT(*) FROM users GROUP BY country HAVING COUNT(*) > 100;\` | | **\`INNER JOIN\`** | Combines rows from two tables where there is a match in both tables based on a related column. | \`SELECT orders.id, customers.name FROM orders INNER JOIN customers ON orders.customer_id = customers.id;\` | | **\`LEFT JOIN\`** | Returns all records from the left table, and the matched records from the right table (fills with NULL if no match). | \`SELECT customers.name, orders.id FROM customers LEFT JOIN orders ON customers.id = orders.customer_id;\` | --- ## 2. Common Aggregate Functions for Requests These functions are often paired with \`SELECT\` statements to compute calculations on your data. | Function | Description | Example | | :--- | :--- | :--- | | **\`COUNT()\`** | Returns the number of rows that match a specified criterion. | \`SELECT COUNT(id) FROM users;\` | | **\`SUM()\`** | Returns the total sum of a numeric column. | \`SELECT SUM(quantity) FROM order_details;\` | | **\`AVG()\`** | Returns the average value of a numeric column. | \`SELECT AVG(price) FROM products;\` | | **\`MIN()\` / \`MAX()\`** | Returns the smallest / largest value of the selected column. | \`SELECT MIN(price), MAX(price) FROM products;\` | --- ## 3. Basic Environment & Discovery Commands Before you can request data, you often need to navigate the database environment to see what tables and structures are available. \`\`\`sql -- List all databases on the server SHOW DATABASES; -- Select a specific database to work with USE database_name; -- List all tables inside the selected database SHOW TABLES; -- View a table's structure (columns, data types, keys) DESCRIBE table_name; \`\`\` `3b:T968,note2 = md` Ce script Jupyter Notebook permet de récupérer de manière automatisée la liste des stations météo uniques (\`NOM_USUEL\`) par département à partir de l'API Data.gouv.fr pour la période 2025-2026 et l'url .parquet associé. \`\`\`python import requests import re import csv import pandas as pd from io import BytesIO DATASET_ID = "donnees-climatologiques-de-base-quotidiennes" API_BASE = "https://www.data.gouv.fr/api/1" # --- 1. Récupérer les liens parquet --- resp = requests.get(f"{API_BASE}/datasets/{DATASET_ID}/") data = resp.json() resources = data.get("resources", []) pattern = re.compile(r"QUOT_departement_\\d+_periode_2025-2026_RR-T-Vent", re.IGNORECASE) parquet_links = [] for r in resources: title = r.get("title", "") if not pattern.search(title): continue extras = r.get("extras", {}) parquet_url = extras.get("analysis:parsing:parquet_url") or r.get("analysis:parsing:parquet_url") if parquet_url: dept = re.search(r"departement_(\\d+)", title, re.IGNORECASE) parquet_links.append({ "departement": dept.group(1) if dept else "", "title": title, "url": parquet_url }) parquet_links.sort(key=lambda x: x["departement"].zfill(3)) print(f"✅ {len(parquet_links)} fichiers parquet trouvés") # --- 2. Ouvrir chaque parquet et extraire les NOM_USUEL uniques --- rows = [] for i, item in enumerate(parquet_links): dept = item["departement"] title = item["title"] url = item["url"] print(f"[{i+1}/{len(parquet_links)}] Département {dept}...") try: r = requests.get(url, timeout=30) r.raise_for_status() df = pd.read_parquet(BytesIO(r.content), columns=["NOM_USUEL"]) noms = df["NOM_USUEL"].dropna().unique() for nom in sorted(noms): rows.append({ "departement": dept, "NOM_USUEL": nom, "title": title, "url": url }) except Exception as e: print(f" ⚠️ Erreur dept {dept}: {e}") # --- 3. Sauvegarder en CSV --- with open("stations_nom_usuel.csv", "w", newline="", encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=["departement", "NOM_USUEL", "title", "url"]) writer.writeheader() writer.writerows(rows) print(f"\\n✅ {len(rows)} stations exportées dans stations_nom_usuel.csv") \`\`\` `3c:T8e7,note3 = md`### Glossaire des variables Météo-France **Localisation et Identification** * **NUM_POSTE** : Numéro Météo-France du poste (8 chiffres). * **NOM_USUEL** : Nom de la station. * **LAT** : Latitude (degrés et millionièmes, négative au Sud). * **LON** : Longitude (degrés et millionièmes, négative à l'Ouest de Greenwich). * **ALTI** : Altitude du pied de l'abri ou du pluviomètre (en m). --- **Mesures Temporelles et Précipitations** * **AAAAMMJJ** : Date de la mesure (Année-Mois-Jour). * **RR** : Précipitations sur 24h (de 06h J à 06h J+1, affectées au jour J) (en mm et 1/10). * **DRR** : Durée totale des précipitations (en mn). --- **Températures (sous abri, en °C et 1/10)** * **TN / HTN** : Température minimale et son heure (hhmm). * **TX / HTX** : Température maximale et son heure (hhmm). * **TM** : Moyenne quotidienne des températures horaires. * **TNTXM** : Moyenne arithmétique (TN+TX)/2. * **TAMPLI** : Amplitude thermique quotidienne (TX - TN). * **TNSOL** : Température minimale à 10 cm du sol. * **TN50** : Température minimale à 50 cm du sol. * **DG** : Durée de gel (T ≤ 0°C) (en mn). --- **Vents (en m/s et 1/10, directions en rose de 360)** * **FFM** : Vent moyen sur 10 mn à 10 m de hauteur. * **FF2M** : Vent moyen sur 10 mn à 2 m de hauteur. * **FXY / DXY / HXY** : Force max, direction et heure du vent moyen (10 mn) à 10 m. * **FXI / DXI / HXI** : Force max, direction et heure du vent instantané à 10 m. * **FXI2 / DXI2 / HXI2** : Force max, direction et heure du vent instantané à 2 m. * **FXI3S / DXI3S / HXI3S** : Force max (moyennée sur 3s), direction et heure à 10 m. --- ### Codes Qualité (ex: QT) | Code | Signification | | :--- | :--- | | **9** | **Filtrée** : Passé les contrôles de premier niveau. | | **0** | **Protégée** : Validée définitivement par un climatologue. | | **1** | **Validée** : Validée par contrôle automatique ou humain. | | **2** | **Douteuse** : En cours de vérification suite à un contrôle auto. | > **Note technique :** Les valeurs respectent généralement la résolution de l'appareil de mesure. 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${note2}

`;\n\n plotContainer.style.display = \"none\";\n\n button.onclick = () => {\n const isHidden = plotContainer.style.display === \"none\";\n plotContainer.style.display = isHidden ? \"block\" : \"none\";\n button.textContent = isHidden ? \"masquer\" : \"script python\";\n };\n\n return html`${button}${plotContainer}`;\n})()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":395,"value":"viewof dept = Inputs.select(liste_dept, {\n label: \"Choisir un département\",\n value: \"31\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":148,"value":"viewof name = Inputs.select(liste_stations, {\n label: \"Choisir une station\",\n value: \"TOULOUSE-BLAGNAC - 31\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":368,"value":"viewof periode = Inputs.radio([\"2025-2026\", \"2025\", \"2026\", \"J-30\"], {\n label: \"Choisir une période\",\n value: \"2025-2026\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":511,"value":"chart_t = {\n const selected_variable = \"T-maximales et minimales\";\n const type = selected_variable.split(\"-\")[0];\n const title = selected_variable.split(\"-\")[1];\n\n const today = new Date();\n\n const maxDate = d3.max(data, (d) => d.date);\n const minDate = d3.min(data, (d) => d.date);\n\n const diffDays = (maxDate - minDate) / (1000 * 60 * 60 * 24);\n console.log(\"diff\", diffDays);\n\n if (diffDays < 120) {\n return createTempPlot(data, type, title);\n } else {\n return createTempPlotLisse(data, type, title);\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":926,"value":"chart_p_cum = {\n const selected_variable = \"RR_cum-Précipitations cumulées\";\n const type = selected_variable.split(\"-\")[0];\n const title = selected_variable.split(\"-\")[1];\n return createRainPlot(data, type, title);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":975,"value":"chart_p_duree = {\n const selected_variable = \"RR_cum- Durée de précipitations cumulées\";\n const type = selected_variable.split(\"-\")[0];\n const title = selected_variable.split(\"-\")[1];\n return createDurationPlot(data, type, title);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":770,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":251,"value":"__","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":141,"value":"stations_nom_usuel = FileAttachment(\"stations_nom_usuel@1.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":146,"value":"liste_stations = stations_nom_usuel\n .filter((d) => (dept == \"Tous\" ? d : d.departement == dept))\n .map((d) => d.NOM_USUEL + \" - \" + d.departement)\n .sort()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":397,"value":"liste_dept = [\n \"Tous\",\n ...[...new Set(stations_nom_usuel.map((d) => d.departement))].sort()\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":182,"value":"selected_station = stations_nom_usuel.find(\n (d) => d.NOM_USUEL == name.split(\" -\")[0]\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":156,"value":"selected_url_station = selected_station.url","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":227,"value":"(() => {\n const button = html``;\n const plotContainer = html`

${note1}

${note3}

`;\n\n plotContainer.style.display = \"none\";\n\n button.onclick = () => {\n const isHidden = plotContainer.style.display === \"none\";\n plotContainer.style.display = isHidden ? \"block\" : \"none\";\n button.textContent = isHidden ? \"masquer\" : \"Variables météo \";\n };\n\n return html`${button}${plotContainer}`;\n})()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"results = db.query(\n `\n SELECT NOM_USUEL,AAAAMMJJ AS date, LAT, LON, TX, TN, RR, DRR, FXY,DXY\n FROM read_parquet('${selected_url_station}')\n WHERE NOM_USUEL = '${selected_station.NOM_USUEL}'\n ORDER BY date\n `\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":359,"value":"function cum_rr(file) {\n // 1. On crée une copie et on trie par date pour un cumul chronologique exact\n const sortedData = [...file].sort((a, b) => a.date - b.date);\n\n let runningTotalRR = 0;\n let runningTotalDRR = 0;\n\n // 2. On calcule les deux cumuls dans la même boucle .map\n return sortedData.map((d) => {\n runningTotalRR += d.RR || 0;\n runningTotalDRR += d.DRR || 0;\n\n return {\n ...d,\n RR_cum: runningTotalRR,\n DRR_cum: runningTotalDRR\n };\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":217,"value":"temp1 = results\n .map((row) => ({ ...row }))\n .sort((a, b) => a.AAAAMMJJ - b.AAAAMMJJ)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":377,"value":"temp2 = {\n if (periode === \"2025-2026\") {\n return cum_rr(temp1);\n }\n\n if (periode === \"2025\") {\n // Extrait l'année et compare à 2025\n return cum_rr(temp1.filter((d) => d.date.getFullYear() === 2025));\n }\n\n if (periode === \"2026\") {\n // Extrait l'année et compare à 2026\n return cum_rr(temp1.filter((d) => d.date.getFullYear() === 2026));\n }\n\n if (periode === \"J-30\") {\n // Calcule le timestamp d'il y a 30 jours (en millisecondes)\n const limiteTimestamp = new Date().getTime() - 30 * 24 * 60 * 60 * 1000;\n\n // Compare le timestamp de chaque ligne avec la limite\n return cum_rr(temp1.filter((d) => d.date.getTime() >= limiteTimestamp));\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":627,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":687,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":685,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":323,"value":"__","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":204,"value":"__","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":332,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":604,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":924,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":972,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":485,"value":"frLocale = d3.timeFormatLocale({\n months: [\n \"janvier\",\n \"février\",\n \"mars\",\n \"avril\",\n \"mai\",\n \"juin\",\n \"juillet\",\n \"août\",\n \"septembre\",\n \"octobre\",\n \"novembre\",\n \"décembre\"\n ],\n shortMonths: [\n \"janv.\",\n \"févr.\",\n \"mars\",\n \"avr.\",\n \"mai\",\n \"juin\",\n \"juil.\",\n \"août\",\n \"sept.\",\n \"oct.\",\n \"nov.\",\n \"déc.\"\n ],\n days: [],\n shortDays: [],\n dateTime: \"\",\n date: \"\",\n time: \"\",\n periods: []\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":354,"value":"__","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":45,"value":"db = await DuckDBClient.of(); // connexion vide, prête pour read_parque\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":30,"value":"import { DuckDBClient } from \"@observablehq/duckdb\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":320,"value":"__","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":229,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":297,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":442,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W3d","stdlib":"1"}} 30:"$2f:body"