📷 instagram.com/nestor2509
Public
Edited
Nov 7, 2022
Importers
chart = DonutChart(population, {
name: d => d.name,
value: d => d.value,
width,
height: 500
})
population = FileAttachment("population-by-age.csv").csv({typed: true})
// Copyright 2021 Observable, Inc.
// Released under the ISC license.
// https://observablehq.com/@d3/donut-chart
function DonutChart(
data,
{
name = ([x]) => x, // given d in data, returns the (ordinal) label
value = ([, y]) => y, // given d in data, returns the (quantitative) value
title, // given d in data, returns the title text
width = 640, // outer width, in pixels
height = 400, // outer height, in pixels
innerRadius = Math.min(width, height) / 3, // inner radius of pie, in pixels (non-zero for donut)
outerRadius = Math.min(width, height) / 2, // outer radius of pie, in pixels
labelRadius = (innerRadius + outerRadius) / 2, // center radius of labels
format = ",", // a format specifier for values (in the label)
names, // array of names (the domain of the color scale)
colors, // array of colors for names
stroke = innerRadius > 0 ? "none" : "white", // stroke separating widths
strokeWidth = 1, // width of stroke separating wedges
strokeLinejoin = "round", // line join of stroke separating wedges
padAngle = stroke === "none" ? 1 / outerRadius : 0 // angular separation between wedges
} = {}
) {
// Compute values.
const N = d3.map(data, name);
const V = d3.map(data, value);
const I = d3.range(N.length).filter((i) => !isNaN(V[i]));
// Unique the names.
if (names === undefined) names = N;
names = new d3.InternSet(names);
// Chose a default color scheme based on cardinality.
if (colors === undefined) colors = d3.schemeSpectral[names.size];
if (colors === undefined)
colors = d3.quantize(
(t) => d3.interpolateSpectral(t * 0.8 + 0.1),
names.size
);
// Construct scales.
const color = d3.scaleOrdinal(names, colors);
// Compute titles.
if (title === undefined) {
const formatValue = d3.format(format);
title = (i) => `${N[i]}\n${formatValue(V[i])}`;
} else {
const O = d3.map(data, (d) => d);
const T = title;
title = (i) => T(O[i], i, data);
}
// Construct arcs.
const arcs = d3
.pie()
.padAngle(padAngle)
.sort(null)
.value((i) => V[i])(I);
const arc = d3.arc().innerRadius(innerRadius).outerRadius(outerRadius);
const arcLabel = d3.arc().innerRadius(labelRadius).outerRadius(labelRadius);
const svg = d3
.create("svg")
.attr("width", width)
.attr("height", height)
.attr("viewBox", [-width / 2, -height / 2, width, height])
.attr("style", "max-width: 100%; height: auto; height: intrinsic;");
svg
.append("g")
.attr("stroke", stroke)
.attr("stroke-width", strokeWidth)
.attr("stroke-linejoin", strokeLinejoin)
.selectAll("path")
.data(arcs)
.join("path")
.attr("fill", (d) => color(N[d.data]))
.attr("d", arc)
.attr("fill-opacity", 0.15)
.append("title")
.text((d) => title(d.data));
svg
.append("g")
.attr("font-family", "sans-serif")
.attr("font-size", 13)
.attr("text-anchor", "middle")
.selectAll("text")
.data(arcs)
.join("text")
.attr("transform", (d) => `translate(${arcLabel.centroid(d)})`)
.selectAll("tspan")
.data((d) => {
const lines = `${title(d.data)}`.split(/\n/);
return d.endAngle - d.startAngle > 0.25 ? lines : lines.slice(0, 1);
})
.join("tspan")
.attr("fill", "#493284")
// .attr("stroke", "#999")
.attr("x", 0)
.attr("y", (_, i) => `${i * 1.1}em`)
.attr("font-weight", (_, i) => (i ? null : "bold"))
.text((d) => d);
return Object.assign(svg.node(), { scales: { color } });
}
import {howto} from "@d3/example-components"
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.
