chart = {
const svg = d3.select(DOM.svg(width, height));
svg.append("g")
.call(xAxis);
svg.append("g")
.call(yAxis);
const group = svg.append("g")
.selectAll("g")
.data(data.series)
.enter().append("g")
.attr("transform", d => `translate(0,${y(d.name) + 1})`);
group.append("path")
.attr("fill", "#ddd")
.attr("d", d => area(d.values));
group.append("path")
.attr("fill", "none")
.attr("stroke", "black")
.attr("d", d => line(d.values));
return svg.node();
}
overlap = 8
height = data.series.length * 17
margin = ({top: 40, right: 20, bottom: 30, left: 120})
x = d3.scaleTime()
.domain(d3.extent(data.dates))
.range([margin.left, width - margin.right])
y = d3.scalePoint()
.domain(data.series.map(d => d.name))
.range([margin.top, height - margin.bottom])
z = d3.scaleLinear()
.domain([0, d3.max(data.series, d => d3.max(d.values))]).nice()
.range([0, -overlap * y.step()])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x)
.ticks(width / 80)
.tickSizeOuter(0))
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y).tickSize(0).tickPadding(4))
.call(g => g.select(".domain").remove())
area = d3.area()
.curve(d3.curveBasis)
.defined(d => !isNaN(d))
.x((d, i) => x(data.dates[i]))
.y0(0)
.y1(d => z(d))
line = area.lineY1()
timeParse = d3.timeParse("%Y-%m-%d")
data = {
const data = await d3.csv(
"https://gist.githubusercontent.com/EricBound/d2c5a870d22f09c204a8fa378fe58024/raw/db8236be77413725cbaee37c8e5a0b1febaccd43/seasonal_imports.csv",
({name, date, amount}) =>
({name, date, value: +amount})
);
const dates = d3.nest()
.key(d => d.date)
.entries(data)
.map(d => new Date(timeParse(d.key)))
.sort(d3.ascending);
const values = d3.nest()
.key(d => d.name)
.key(d => d.date)
.rollup(v => v[0].value)
.map(data);
return {
series: values.entries().map(({key, value}) => ({
name: key,
values: dates.map(d => value.get(+d))
})),
dates
};
}
d3 = require("d3@5")
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.
