chart = {
// Specify the chart’s dimensions (except for the height).
const marginTop = 30;
const marginRight = 20;
const marginBottom = 0;
const marginLeft = 100;
// Determine the series that need to be stacked.
const series = d3.stack()
.keys(d3.union(data.map(d => d.answer))) // distinct series keys, in input order
.value(([, D], key) => D.get(key).population) // get value for each series key and stack
.offset(d3.stackOffsetExpand)
(d3.index(data, d => d.state, d => d.answer)); // group by stack then series key
// Compute the height from the number of stacks.
const height = series[0].length * 25 + marginTop + marginBottom;
// Prepare the scales for positional and color encodings.
const x = d3.scaleLinear()
.domain([0, d3.max(series, d => d3.max(d, d => d[1]))])
.range([marginLeft, width - marginRight]);
const y = d3.scaleBand()
.domain(d3.groupSort(data, (D) => -D.find(d => d.answer === "Mostly Help").population / d3.sum(D, d => d.population), d => d.state))
.range([marginTop, height - marginBottom])
.padding(0.08);
const color = d3.scaleOrdinal(WRPcolours)
.domain(series.map(d => d.key))
.unknown("#ccc");
// A function to format the value in the tooltip.
const formatValue = x => isNaN(x) ? "N/A" : x.toLocaleString("en")
// Create the SVG container.
const svg = d3.create("svg")
.attr("width", width)
.attr("height", height)
.attr("viewBox", [0, 0, width, height])
.attr("style", "max-width: 100%; height: auto;");
// Append a group for each series, and a rect for each element in the series.
svg.append("g")
.selectAll()
.data(series)
.join("g")
.attr("fill", d => color(d.key))
.selectAll("rect")
.data(D => D.map(d => (d.key = D.key, d)))
.join("rect")
.attr("x", d => x(d[0]))
.attr("y", d => y(d.data[0]))
.attr("height", y.bandwidth())
.attr("width", d => x(d[1]) - x(d[0]))
.append("title")
.text(d => `${d.data[0]} ${d.key}\n${formatValue(d.data[1].get(d.key).population)}`);
// Append the horizontal axis.
svg.append("g")
.attr("transform", `translate(0,${marginTop})`)
.call(d3.axisTop(x).ticks(width / 100, "%"))
.call(g => g.selectAll(".domain").remove());
// Append the vertical axis.
svg.append("g")
.attr("transform", `translate(${marginLeft},0)`)
.call(d3.axisLeft(y).tickSizeOuter(0))
.call(g => g.selectAll(".domain").remove());
// Return the chart with the color scale as a property (for the legend).
return Object.assign(svg.node(), {scales: {color}});
}
data = {
const data = await FileAttachment("aihelpharm.csv").csv({typed: true});
return data.columns.slice(1).flatMap((answer) => data.map((d) => ({state: d.name, answer, population: d[answer]})));
}
WRPcolours = ["#E5006E", "#007E7E", "#3F637E", "#717171","#537C36","#D3702D","#993595"]
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.
