Public
Edited
Aug 1, 2023
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Bubble map
chart = {
// Join the geographic shapes and the population data.
const data = population.map((d) => ({
...d,
county: countymap.get(d.fips),
state: statemap.get(d.state)
}))
.filter(d => d.county)
.sort((a, b) => d3.descending(a.population, b.population));
// Construct the radius scale.
const radius = d3.scaleSqrt([0, d3.max(data, d => d.population)], [0, 40]);
// Construct a path generator.
const path = d3.geoPath();
// Create the SVG container. Its dimensions correspond to the bounding-box
// of the pre-projected US shapefile.
const svg = d3.create("svg")
.attr("width", 975)
.attr("height", 610)
.attr("viewBox", [0, 0, 975, 610])
.attr("style", "width: 100%; height: auto; height: intrinsic;");
// Create the cartographic background layers.
svg.append("path")
.datum(topojson.feature(us, us.objects.nation))
.attr("fill", "#ddd")
.attr("d", path);
svg.append("path")
.datum(topojson.mesh(us, us.objects.states, (a, b) => a !== b))
.attr("fill", "none")
.attr("stroke", "white")
.attr("stroke-linejoin", "round")
.attr("d", path);
// Create the legend.
const legend = svg.append("g")
.attr("fill", "#777")
.attr("transform", "translate(915,608)")
.attr("text-anchor", "middle")
.style("font", "10px sans-serif")
.selectAll()
.data(radius.ticks(4).slice(1))
.join("g");
legend.append("circle")
.attr("fill", "none")
.attr("stroke", "#ccc")
.attr("cy", d => -radius(d))
.attr("r", radius);
legend.append("text")
.attr("y", d => -2 * radius(d))
.attr("dy", "1.3em")
.text(radius.tickFormat(4, "s"));
// Add a circle for each county, with a title (tooltip).
const format = d3.format(",.0f");
svg.append("g")
.attr("fill", "brown")
.attr("fill-opacity", 0.5)
.attr("stroke", "#fff")
.attr("stroke-width", 0.5)
.selectAll()
.data(data)
.join("circle")
.attr("transform", d => `translate(${centroid(d.county)})`)
.attr("r", d => radius(d.population))
.append("title")
.text(d => `${d.county.properties.name}, ${d.state.properties.name}
${format(d.population)}`);
return svg.node();
}
population = FileAttachment("population.json").json()
.then((data) =>
data
.slice(1) // removes a header line
.map(([p, state, county]) => ({
state,
fips: `${state}${county}`,
population: +p
}))
)
centroid = {
const path = d3.geoPath();
return feature => path.centroid(feature);
}
us = FileAttachment("counties-albers-10m.json").json()
nation = topojson.feature(us, us.objects.nation)
statemap = new Map(topojson.feature(us, us.objects.states).features.map(d => [d.id, d]))
countymap = new Map(topojson.feature(us, us.objects.counties).features.map(d => [d.id, d]))
statemesh = topojson.mesh(us, us.objects.states, (a, b) => a !== b)
Plot.plot({
width: 975,
projection: "identity",
marks: [
Plot.geo(nation, { fill: "#eee" }),
Plot.geo(statemesh, { stroke: "white" }),
Plot.dot(population, Plot.centroid({r: "population", geometry: ({fips}) => countymap.get(fips)}))
]
})
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
