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 markContainersinsetsPath markText markInteractivityTooltipsLegendsCircle markWhy 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
Ridgelines map
viz = require(`geoviz@0.5.0`)
xyz
svg = {
// Font
viz.tool.addfonts([
{
fontFamily: "Wallpoet",
url: await FileAttachment("Wallpoet-Regular.ttf").url()
}
]);
// Container
let svg = viz.create({
projection: d3.geoIdentity().reflectY(true),
domain: [
[-135, 75],
[165, -50]
],
margin: [-20, 0, 0, 0],
background: "#333335"
});
return svg;
}
l = viz.tool.ridge(xyz, {
z: "value",
k: k,
projection: svg.projection
})
svg.path({
id: "ridge",
coords: "svg",
data: l,
stroke: "#ffb619",
strokeWidth: 0.7,
fill: "#262728"
})
svg.legend.spikes({
id: "legspikes",
data: xyz.map((d) => d.value),
k,
spike_straight: 1,
spike_width: 10,
spike_stroke: "#ffb619",
title: "Number of\ninhabitants",
text_fill: "#ffb619",
values_fill: "#ffb619",
pos: [50, 240]
})
viz.header(svg, {
id: "header",
rect_fillOpacity: 1,
fontSize: 45,
fillOpacity: 1,
fill: "#ffb619",
fontFamily: "Wallpoet",
text: "- World Population -",
background_fill: "#333335",
background_stroke: "#333335"
})
viz.footer(svg, {
id: "footer",
text: "Map design: Nicolas LAMBERT, 2023\nSources: Gridded Population of the World, Version 4 (GPWv4): Population Count, Revision 11",
textAnchor: "end",
fontSize: 8,
margin: 8,
fill: "#ffb619",
background_fill: "#333335",
background_stroke: "#333335"
})
xyz = grid.filter((d) => d.value > filter)
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.