Published
Edited
Sep 4, 2020
chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
const bar = svg.append("g")
.attr("fill", "#d984db")
.selectAll("rect")
.data(data)
.join("rect")
.style("mix-blend-mode", "multiply")
.attr("x", d => x(d.name))
.attr("y", d => y(d.value))
.attr("height", d => y(0) - y(d.value))
.attr("width", x.bandwidth());
const gx = svg.append("g")
.call(xAxis);
const gy = svg.append("g")
.call(yAxis);
return Object.assign(svg.node(), {
update(order) {
x.domain(data.sort(order).map(d => d.name));
const t = svg.transition()
.duration(750);
bar.data(data, d => d.name)
.order()
.transition(t)
.delay((d, i) => i * 20)
.attr("x", d => x(d.name));
gx.transition(t)
.call(xAxis)
.selectAll(".tick")
.delay((d, i) => i * 20);
}
});
}
chart.update(order)
data = d3.csvParse(await FileAttachment("04_How much does the avg person own? - BarChart-3.csv").text(), ({country, responses}) => ({name: country, value: +responses}))
x = d3.scaleBand()
.domain(data.map(d => d.name))
.range([margin.left, width - margin.right])
.padding(0.1)
y = d3.scaleLinear()
.domain([0, d3.max(data, d => d.value)]).nice()
.range([height - margin.bottom, margin.top])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x).tickSizeOuter(0))
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y))
.call(g => g.select(".domain").remove())
height = 500
margin = ({top: 20, right: 0, bottom: 30, left: 40})
d3 = require("d3@6")
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.
