chart = {
const svg = d3.create("svg").attr("viewBox", [0, 0, width, height]);
svg
.append("g")
.selectAll("g")
.data(series)
.join("g")
.attr("fill", showColors ? ({ key }) => color(key) : 'steelblue')
.call(g =>
g
.selectAll("rect")
.data(d => d)
.join("rect")
.attr("x", d => x(d.data.year))
.attr("y", d => y(d[1]))
.attr("width", x.bandwidth() - 1)
.attr("height", d => y(d[0]) - y(d[1]))
.append("title")
.text(
d => `${d.data.name}, ${d.data.year}
${formatNumber(d.data.value)}`
)
);
svg.append("g").call(xAxis);
svg.append("g").call(yAxis);
return svg.node();
}
data = Object.assign(
(await d3.csv(
'https://kb.twopointzero.us/datasets/riaa-music-sales-volume.csv',
({ Format, Year, ["Value (For Charting)"]: Value, Metric }) => ({
name: Format,
year: +Year,
value: +Value * 1e6,
metric: Metric
})
)).filter(r => r.metric === 'Units' && r.name),
{ y: "Units (Billions)" }
)
colors = new Map([
["LP/EP", "#2A5784"],
["Vinyl Single", "#43719F"],
["8 - Track", "#5B8DB8"],
["Cassette", "#7AAAD0"],
["Cassette Single", "#9BC7E4"],
["Other Tapes", "#BADDF1"],
["Kiosk", "#E1575A"],
["CD", "#EE7423"],
["CD Single", "#F59D3D"],
["SACD", "#FFC686"],
["DVD Audio", "#9D7760"],
["Music Video (Physical)", "#F1CF63"],
["Download Album", "#7C4D79"],
["Download Single", "#9B6A97"],
["Ringtones & Ringbacks", "#BE89AC"],
["Download Music Video", "#D5A5C4"],
// ["Other Digital", "#EFC9E6"],
// ["Synchronization", "#BBB1AC"],
["Paid Subscriptions", "#24693D"],
// ["On-Demand Streaming (Ad-Supported)", "#398949"],
// ["Other Ad-Supported Streaming", "#61AA57"],
// ["SoundExchange Distributions", "#7DC470"],
// ["Limited Tier Paid Subscription", "#B4E0A7"]
])
series = d3
.stack()
.keys(Array.from(colors.keys()).reverse())
.value((group, key) => group.get(key).value)
.order(d3.stackOrderReverse)(
Array.from(d3.rollup(data, ([d]) => d, d => d.year, d => d.name).values())
)
.map(s => (s.forEach(d => (d.data = d.data.get(s.key))), s))
x = d3.scaleBand()
.domain(data.map(d => d.year))
.rangeRound([margin.left, width - margin.right])
y = d3.scaleLinear()
.domain([0, d3.max(series, d => d3.max(d, d => d[1]))]).nice()
.range([height - margin.bottom, margin.top])
color = d3.scaleOrdinal()
.domain(Array.from(colors.keys()))
.range(Array.from(colors.values()))
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x)
.tickValues(d3.ticks(...d3.extent(x.domain()), width / 80))
.tickSizeOuter(0))
yAxis = g =>
g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y).tickFormat(x => (x / 1e9).toFixed(1)))
.call(g => g.select(".domain").remove())
.call(g =>
g
.select(".tick:last-of-type text")
.clone()
.attr("x", 3)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.text(data.y)
)
formatNumber = x => (+(x / 1e9).toFixed(2) >= 1)
? `${(x / 1e9).toFixed(2)}B`
: `${(x / 1e6).toFixed(0)}M`
totals = new Map(
[...d3.group(data, d => d.name).entries()].map(([k, v]) => [
k,
v.reduce((acc, r) => r.value + acc, 0)
])
)
peaks = new Map(
[...d3.group(data, d => d.name).entries()].map(([k, v]) => [
k,
v.reduce((max, r) => (r.value > max.value ? r : max), {
value: 0,
year: 'N/A'
})
])
)
height = 500
margin = ({top: 20, right: 30, bottom: 30, left: 30})
d3 = require("d3@5", "d3-array@2")
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.
