chart = {
// Specify the chart’s dimensions.
const width = 928;
const height = 500;
const marginTop = 20;
const marginRight = 30;
const marginBottom = 30;
const marginLeft = 40;
// Create the horizontal scale *x*.
const x = d3.scaleLinear()
.domain(d3.extent(data)).nice()
.range([marginLeft, width - marginRight]);
// Bin the data on *x*.
const bins = d3.bin()
.domain(x.domain())
.thresholds(thresholds)
(data);
// Compute the vertical scale *y*.
const y = d3.scaleLinear()
.domain([0, d3.max(bins, d => d.length) / data.length])
.range([height - marginBottom, marginTop]);
// Create the SVG container.
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height])
.attr("width", width)
.attr("height", height)
.attr("style", "max-width: 100%; height: auto;");
// Append a rect for each bin.
svg.append("g")
.attr("fill", "#bbb")
.selectAll("rect")
.data(bins)
.join("rect")
.attr("x", d => x(d.x0) + 1)
.attr("y", d => y(d.length / data.length))
.attr("width", d => x(d.x1) - x(d.x0) - 1)
.attr("height", d => y(0) - y(d.length / data.length));
// Append the kernel-density-estimation line.
const line = d3.line()
.curve(d3.curveBasis)
.x(d => x(d[0]))
.y(d => y(d[1]));
svg.append("path")
.datum(density)
.attr("fill", "none")
.attr("stroke", "#000")
.attr("stroke-width", 1.5)
.attr("stroke-linejoin", "round")
.attr("d", line);
// Append the axes.
svg.append("g")
.attr("transform", `translate(0,${height - marginBottom})`)
.call(d3.axisBottom(x))
.call(g => g.append("text")
.attr("x", width - marginRight)
.attr("y", -6)
.attr("fill", "#000")
.attr("text-anchor", "end")
.attr("font-weight", "bold")
.text("Time between eruptions (min.)"));
svg.append("g")
.attr("transform", `translate(${marginLeft},0)`)
.call(d3.axisLeft(y).ticks(null, "%"))
.call(g => g.select(".domain").remove());
return svg.node();
}
function kde(kernel, thresholds, data) {
return thresholds.map(t => [t, d3.mean(data, d => kernel(t - d))]);
}
function epanechnikov(bandwidth) {
return x => Math.abs(x /= bandwidth) <= 1 ? 0.75 * (1 - x * x) / bandwidth : 0;
}
thresholds = d3.ticks(...d3.nice(...d3.extent(data), 10), 40)
density = kde(epanechnikov(bandwidth), thresholds, data)
data = FileAttachment("faithful.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.
