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 🖥️
Map projectionsh3-jsSymbolsThe draw() functionsquareProportional symbolsSpike markTypologyChoroplethLayout marksHandle geometriesSVG filters and clipTile markContainersPath markText markInteractivityTooltipsLegendsCircle markRidgelines mapWhy it's better not to add scalebars to world mapsNight and dayPan and zoomCharging points for electric vehicles in ParisLet's design a "dot cartogram"Hello geovizWorld Population
insets
china = viz.tool.featurecollection(
world.features.filter((d) => d.properties.ISO3 == "CHN")
)
{
let svg = viz.create({ domain: china, margin: 30 });
svg.path({ datum: world, fill: "#CCC" });
svg.path({ datum: china, fill: "#38896F" });
let inset = viz.container.create({
parent: svg,
pos: [795, 395],
width: 200,
projection: d3.geoOrthographic().rotate([-100, -30])
});
inset.path({ datum: world, fill: "#CCC" });
inset.path({ datum: china, fill: "#38896F" });
inset.outline({ fill: "none", stroke: "#38896F", strokeWidth: 3 });
return svg.render();
}
{
const prj = d3.geoConicConformal().center([2.454071, 46.279229]);
let svg = viz.create({
domain: france,
projection: prj,
margin: [100, 100, 0, 0]
});
svg.path({ datum: france, fill: "#CCC" });
svg.circle({
data: france,
r: "pop",
fill: "#38896F",
k: 40,
tip: "$pop"
});
let inset = viz.container.create({
parent: svg,
pos: [520, 10],
width: 300,
projection: prj,
domain: idf
//projection: d3.geoOrthographic().rotate([-100, -30])
});
inset.path({ data: idf, fill: "#CCC", stroke: "white" });
inset.circle({
data: idf,
r: "pop",
fill: "#38896F",
k: 40,
tip: "$pop"
});
return svg.render();
}
idf = viz.tool.featurecollection(
france.features.filter((d) =>
["75", "77", "78", "91", "92", "93", "94", "95"].includes(d.properties.id)
)
)
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.