I love to build dataviz for insight discovery. I also love to put technology to the service of humanity
chart = {
const links = data.links.map(d => Object.create(d));
const nodes = data.nodes.map(d => Object.create(d));
const simulation = d3
.forceSimulation(nodes)
.force("link", d3.forceLink(links).id(d => d.id))
.force("charge", d3.forceManyBody())
.force("center", d3.forceCenter(width / 2, height / 2));
const svg = d3.create("svg").attr("viewBox", [0, 0, width, height]);
const link = svg
.append("g")
.attr("stroke", "#999")
.attr("stroke-opacity", 0.6)
.selectAll("line")
.data(links)
.join("line")
.attr("stroke-width", d => Math.sqrt(d.value));
const node = svg
.append("g")
.attr("stroke", "#fff")
.attr("stroke-width", 1.5)
.selectAll("circle")
.data(nodes)
.join("circle")
.attr("r", 5)
.attr("fill", color)
.call(drag(simulation))
.on("mouseenter", (evt, d) => {
link
.attr("display", "none")
.filter(l => l.source.id === d.id || l.target.id === d.id)
.attr("display", "block");
})
.on("mouseleave", evt => {
link.attr("display", "block");
});
node.append("title").text(d => d.id);
simulation.on("tick", () => {
link
.attr("x1", d => d.source.x)
.attr("y1", d => d.source.y)
.attr("x2", d => d.target.x)
.attr("y2", d => d.target.y);
node.attr("cx", d => d.x).attr("cy", d => d.y);
});
invalidation.then(() => simulation.stop());
return svg.node();
}
data = FileAttachment("miserables.json").json()
height = 600
color = {
const scale = d3.scaleOrdinal(d3.schemeCategory10);
return d => scale(d.group);
}
drag = simulation => {
function dragstarted(event) {
if (!event.active) simulation.alphaTarget(0.3).restart();
event.subject.fx = event.subject.x;
event.subject.fy = event.subject.y;
}
function dragged(event) {
event.subject.fx = event.x;
event.subject.fy = event.y;
}
function dragended(event) {
if (!event.active) simulation.alphaTarget(0);
event.subject.fx = null;
event.subject.fy = null;
}
return d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended);
}
d3 = require("d3@6")
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.