Unlisted
Edited
Oct 4, 2024
change_by_state_counts = FileAttachment(
"change_2022_2034_by_state_wide@2.csv"
).csv({ typed: true })
us = FileAttachment("counties-albers-10m.json").json()
statemesh = topojson.mesh(us, us.objects.states, (a, b) => a !== b)
hierarchy = createHierarchy(data)
{
const hierarchy = createHierarchy(data);
// Create pack layout
const width = 800;
const height = 800;
const pack = d3.pack().size([width, height]).padding(3);
const root = pack(hierarchy);
// Prepare data for plotting
const circles = root.descendants().map((d) => ({
x: d.x,
y: d.y,
r: d.r,
depth: d.depth,
data: d.data
}));
// Create the plot
return Plot.plot({
width,
height,
margin: 1,
style: {
fontFamily: "sans-serif",
fontSize: 10
},
marks: [
Plot.dot(circles, {
x: "x",
y: "y",
r: "r",
fill: (d) => d3.schemeCategory10[d.depth],
fillOpacity: 0.7,
stroke: "#ccc",
title: (d) =>
`${d.data.domain}\nSOC: ${d.data.soc}\nJobs: ${d.data.jobs}`
}),
Plot.text(circles, {
x: "x",
y: "y",
text: (d) => d.data.domain,
fontSize: (d) => Math.max(8, Math.min(2 * d.r, 24)),
clip: true,
overflow: "hidden",
width: (d) => d.r * 2,
height: (d) => d.r * 2
})
]
});
}
import {Sunburst} from "@d3/sunburst"
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.