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Nicolas Lambert
Hi. I'm Nicolas Lambert, research engineer in geographic information science at CNRS (France). My job is to draw maps and teach cartography at the university. I am a geographer 🌎, and not really a developer 🖥️
Public
Bosphore
Edited
Oct 17, 2023
19
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Voici du texte en *italic* ou en __gras__ avec un [lien](https://observablehq.com/).
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<div>ceci est du texte surligné en <span style="background-color:tomato; color:white">rouge</span>.</div>
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<canvas id="myCanvas" width="100" height ="100" style="border:1px
solid #000000; background-color: steelblue;"></canvas>
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<svg viewBox="0 0 1000 100" xmlns="http://www.w3.org/2000/svg">
<rect x="0" y="0" width="100px" height="100px" fill="#F2CD3B" stroke="#06000C" />
</svg>
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tex`_{n+1} = 2^{n+1}`
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c = \pm\sqrt{a^2 + b^2}
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a = 10
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b = 6
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c = a + b
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x = {
let val1 = 8;
let val2 = 7;
return val1 * val2;
}
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function sum(a, b) {
return a + b;
}
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sum(10, 30)
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multi = (a, b) => a * b
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multi(3, 8)
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e + d
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d = 5
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e = 5
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viewof color = Inputs.color({ label: "Couleur", value: "#4ab58c" })
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viewof position = Inputs.range([50, 950], {
label: "Position",
step: 1,
value: 50
})
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<svg viewBox="0 0 1000 100" xmlns="http://www.w3.org/2000/svg">
<circle cx=${position} cy="50" r=${radius} fill="${color}"/>
</svg>
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data = FileAttachment("stats.csv").csv({ typed: true })
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Inputs.table(data)
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data2
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cities = d3
.csv(
"https://raw.githubusercontent.com/neocarto/resources/master/datasets/simplemaps_worldcities_basicv1.73/worldcities.csv",
d3.autoType
)
.then((r) => r.filter((d) => +d.population > 1000000))
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world = FileAttachment("countries.json").json()
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Plot.plot({ projection: "equal-earth", marks: [Plot.geo(world)] })
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geo = require("geotoolbox")
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africa = geo.union(geo.filter(world, (d) => d.region == "Africa"))
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buffer = geo.buffer(africa, { dist: k })
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countries_clip = geo.clip(world, { clip: buffer })
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viewof k = Inputs.range([100, 5000], { label: "Distance", step: 100 })
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bertin = require("bertin")
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bertin.draw({
layers: [
{
geojson: world,
fill: "yellow",
stroke: "red"
}
]
})
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bertin.draw({
layers: [
{
type: "bubble", // Essayer type = "simple", type = "square", type = "spikes"
geojson: world,
values: "pop", // <- données quantitatives absolues
fill: "red",
leg_x: 75,
leg_y: 250,
leg_round: -2
},
{
geojson: world,
fill: "#CCC"
}
]
})
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bertin.draw({
params: { projection: "Eckert3" }, // Paramètres généraux (marges, projection, etc.)
layers: [
{ type: "header", text: "La population mondiale" }, // Titre
{ type: "footer", text: "Fait avec bertin.js", anchor: "middle" }, // Source
// COUCHE 1 (cercles)
{
type: "bubble",
geojson: world, // géometrie
k: radiusmax, // Rayon du plus gros cercles
values: "pop", // variable
fill: "#b566ac", // couleur des cercles
stroke: "white", // couleur de contour des cercles
strokeWidth: 0.5, // épaisseur
tooltip: ["$name", "$pop"], // Infobulle
leg_x: 100, // position de la légende (x)
leg_y: 250, // position de la légende (y)
leg_title: "Population des\npays en 2000", // Titre de la légende
leg_round: -3 // arrondi
},
// COUCHE 1 (pays)
{
geojson: world, // géométrie
fill: "white", // couleur de fond
stroke: "none", // cauleur de contour (aucun)
fillOpacity: 0.5 // Opacité
},
{ type: "graticule" }, // Lignes de latitude et longitude
{ type: "outline" } // coutour de la Terre dans la projection
]
})
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bertin.draw({
params: { projection: "Eckert3" }, // Paramètres généraux (marges, projection, etc.)
layers: [
{ type: "header", text: "La population mondiale" }, // Titre
{ type: "footer", text: "Fait avec bertin.js", anchor: "middle" }, // Source
// COUCHE 1 (pays)
{
geojson: world, // géométrie
fill: {
// choropleth
type: "choro",
values: "gdppc",
method: "q6", // essayer "jenks", "quantile", "geometric", "equal"
colors: "Spectral", // Essayer "PuBuGn"
leg_x: 100,
leg_y: 200,
leg_title: "GDP per capita",
leg_roubd: 0
},
tooltip: ["$name", "$gdppc"] // Infobulle
},
{ type: "graticule" }, // Lignes de latitude et longitude
{ type: "outline" } // coutour de la Terre dans la projection
]
})
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import {ForceGraph} from "@d3/force-directed-graph-component"
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