Data Scientist, Author, DataVis, Educator, Speaker, Public Service @ClintonBrownley
https://cbrownley.github.io
chart = {
// Specify the chart’s dimensions.
const width = 928;
const height = width;
const radius = width / 6;
const data = table2Tree(samples, ["category", "subcategory"]);
// Create the color scale.
const color = d3.scaleOrdinal(
d3.quantize(d3.interpolateRainbow, data.children.length + 1)
);
// Compute the layout.
const hierarchy = d3
.hierarchy(data)
.sum((d) => d.value)
.sort((a, b) => b.value - a.value);
const root = d3.partition().size([2 * Math.PI, hierarchy.height + 1])(
hierarchy
);
root.each((d) => (d.current = d));
// Create the arc generator.
const arc = d3
.arc()
.startAngle((d) => d.x0)
.endAngle((d) => d.x1)
.padAngle((d) => Math.min((d.x1 - d.x0) / 2, 0.005))
.padRadius(radius * 1.5)
.innerRadius((d) => d.y0 * radius)
.outerRadius((d) => Math.max(d.y0 * radius, d.y1 * radius - 1));
// Create the SVG container.
const svg = d3
.create("svg")
.attr("viewBox", [-width / 2, -height / 2, width, width])
.style("font", "10px sans-serif");
// Append the arcs.
const path = svg
.append("g")
.selectAll("path")
.data(root.descendants().slice(1))
.join("path")
.attr("fill", (d) => {
while (d.depth > 1) d = d.parent;
return color(d.data.name);
})
.attr("fill-opacity", (d) =>
arcVisible(d.current) ? (d.children ? 0.6 : 0.4) : 0
)
.attr("pointer-events", (d) => (arcVisible(d.current) ? "auto" : "none"))
.attr("d", (d) => arc(d.current));
// Make them clickable if they have children.
path
.filter((d) => d.children)
.style("cursor", "pointer")
.on("click", clicked);
const format = d3.format(",d");
path.append("title").text(
(d) =>
`${d
.ancestors()
.map((d) => d.data.name)
.reverse()
.join("/")}\n${format(d.value)}`
);
const label = svg
.append("g")
.attr("pointer-events", "none")
.attr("text-anchor", "middle")
.style("user-select", "none")
.selectAll("text")
.data(root.descendants().slice(1))
.join("text")
.attr("dy", "0.35em")
.attr("fill-opacity", (d) => +labelVisible(d.current))
.attr("transform", (d) => labelTransform(d.current))
.text((d) => d.data.name);
const parent = svg
.append("circle")
.datum(root)
.attr("r", radius)
.attr("fill", "none")
.attr("pointer-events", "all")
.on("click", clicked);
// Handle zoom on click.
function clicked(event, p) {
parent.datum(p.parent || root);
root.each(
(d) =>
(d.target = {
x0:
Math.max(0, Math.min(1, (d.x0 - p.x0) / (p.x1 - p.x0))) *
2 *
Math.PI,
x1:
Math.max(0, Math.min(1, (d.x1 - p.x0) / (p.x1 - p.x0))) *
2 *
Math.PI,
y0: Math.max(0, d.y0 - p.depth),
y1: Math.max(0, d.y1 - p.depth)
})
);
const t = svg.transition().duration(750);
// Transition the data on all arcs, even the ones that aren’t visible,
// so that if this transition is interrupted, entering arcs will start
// the next transition from the desired position.
path
.transition(t)
.tween("data", (d) => {
const i = d3.interpolate(d.current, d.target);
return (t) => (d.current = i(t));
})
.filter(function (d) {
return +this.getAttribute("fill-opacity") || arcVisible(d.target);
})
.attr("fill-opacity", (d) =>
arcVisible(d.target) ? (d.children ? 0.6 : 0.4) : 0
)
.attr("pointer-events", (d) => (arcVisible(d.target) ? "auto" : "none"))
.attrTween("d", (d) => () => arc(d.current));
label
.filter(function (d) {
return +this.getAttribute("fill-opacity") || labelVisible(d.target);
})
.transition(t)
.attr("fill-opacity", (d) => +labelVisible(d.target))
.attrTween("transform", (d) => () => labelTransform(d.current));
}
function arcVisible(d) {
return d.y1 <= 3 && d.y0 >= 1 && d.x1 > d.x0;
}
function labelVisible(d) {
return d.y1 <= 3 && d.y0 >= 1 && (d.y1 - d.y0) * (d.x1 - d.x0) > 0.03;
}
function labelTransform(d) {
const x = (((d.x0 + d.x1) / 2) * 180) / Math.PI;
const y = ((d.y0 + d.y1) / 2) * radius;
return `rotate(${x - 90}) translate(${y},0) rotate(${x < 180 ? 0 : 180})`;
}
return svg.node();
}
import { table2Tree } from "@john-guerra/table-2-tree"
samples = FileAttachment("SamplesSummary2.csv").csv({typed:true})
//data = FileAttachment("samples@1.json").json()
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.
