Unlisted
Edited
Sep 23, 2024
42 forks
Importers
69 stars
chart = {
const svg = d3.select(DOM.svg(width, height))
.attr("viewBox", `${-width / 2} ${-height * 0.69} ${width} ${height}`)
.style("width", "100%")
.style("height", "auto")
.style("font", "10px sans-serif");
svg.append("g")
.selectAll("g")
.data(d3.stack().keys(data.columns.slice(1))(data))
.join("g")
.attr("fill", d => z(d.key))
.selectAll("path")
.data(d => d)
.join("path")
.attr("d", arc);
svg.append("g")
.call(xAxis);
svg.append("g")
.call(yAxis);
svg.append("g")
.call(legend);
return svg.node();
}
data = d3.csvParse(await FileAttachment("data-2.csv").text(), (d, _, columns) => {
let total = 0;
for (let i = 1; i < columns.length; ++i) total += d[columns[i]] = +d[columns[i]];
d.total = total;
return d;
}).sort((a, b) => b.total - a.total)
arc = d3.arc()
.innerRadius(d => y(d[0]))
.outerRadius(d => y(d[1]))
.startAngle(d => x(d.data.State))
.endAngle(d => x(d.data.State) + x.bandwidth())
.padAngle(0.01)
.padRadius(innerRadius)
x = d3.scaleBand()
.domain(data.map(d => d.State))
.range([0, 2 * Math.PI])
.align(0)
// This scale maintains area proportionality of radial bars
y = d3.scaleRadial()
.domain([0, d3.max(data, d => d.total)])
.range([innerRadius, outerRadius])
z = d3.scaleOrdinal()
.domain(data.columns.slice(1))
.range(["#98abc5", "#8a89a6", "#7b6888", "#6b486b", "#a05d56", "#d0743c", "#ff8c00"])
xAxis = g => g
.attr("text-anchor", "middle")
.call(g => g.selectAll("g")
.data(data)
.enter().append("g")
.attr("transform", d => `
rotate(${((x(d.State) + x.bandwidth() / 2) * 180 / Math.PI - 90)})
translate(${innerRadius},0)
`)
.call(g => g.append("line")
.attr("x2", -5)
.attr("stroke", "#000"))
.call(g => g.append("text")
.attr("transform", d => (x(d.State) + x.bandwidth() / 2 + Math.PI / 2) % (2 * Math.PI) < Math.PI
? "rotate(90) translate(0,16)"
: "rotate(-90) translate(0,-9)")
.text(d => d.State)))
yAxis = g => g
.attr("text-anchor", "end")
.call(g => g.append("text")
.attr("x", -6)
.attr("y", d => -y(y.ticks(10).pop()))
.attr("dy", "-1em")
.text("Population"))
.call(g => g.selectAll("g")
.data(y.ticks(10).slice(1))
.join("g")
.attr("fill", "none")
.call(g => g.append("circle")
.attr("stroke", "#000")
.attr("stroke-opacity", 0.5)
.attr("r", y))
.call(g => g.append("text")
.attr("x", -6)
.attr("y", d => -y(d))
.attr("dy", "0.35em")
.attr("stroke", "#fff")
.attr("stroke-width", 5)
.text(y.tickFormat(10, "s"))
.clone(true)
.attr("fill", "#000")
.attr("stroke", "none")))
legend = g => g.append("g")
.selectAll("g")
.data(data.columns.slice(1).reverse())
.join("g")
.attr("transform", (d, i) => `translate(-40,${(i - (data.columns.length - 1) / 2) * 20})`)
.call(g => g.append("rect")
.attr("width", 18)
.attr("height", 18)
.attr("fill", z))
.call(g => g.append("text")
.attr("x", 24)
.attr("y", 9)
.attr("dy", "0.35em")
.text(d => d))
width = 975
height = width
innerRadius = 180
outerRadius = Math.min(width, height) * 0.67
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.
