md`# Movement of population between provinces in 2019-nCoV
The image shows all patients with 2019-nCoV moving between provinces before February 2. The thickness of each curved line represents a quantity that is repeatedly subdivided by category. The datas come from Chinese provincial and municipal health authorities `
chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
const {nodes, links} = sankey({
nodes: graph.nodes.map(d => Object.assign({}, d)),
links: graph.links.map(d => Object.assign({}, d))
});
svg.append("g")
.selectAll("rect")
.data(nodes)
.join("rect")
.attr("x", d => d.x0)
.attr("y", d => d.y0)
.attr("height", d => d.y1 - d.y0)
.attr("width", d => d.x1 - d.x0)
.append("title")
.text(d => `${d.name}\n${d.value.toLocaleString()}`);
svg.append("g")
.attr("fill", "none")
.selectAll("g")
.data(links)
.join("path")
.attr("d", d3.sankeyLinkHorizontal())
.attr("stroke", d => color(d.names[0]))
.attr("stroke-width", d => d.width)
.style("mix-blend-mode", "multiply")
.append("title")
.text(d => `${d.names.join(" → ")}\n${d.value.toLocaleString()}`);
svg.append("g")
.style("font", "10px sans-serif")
.selectAll("text")
.data(nodes)
.join("text")
.attr("x", d => d.x0 < width / 2 ? d.x1 + 6 : d.x0 - 6)
.attr("y", d => (d.y1 + d.y0) / 2)
.attr("dy", "0.35em")
.attr("text-anchor", d => d.x0 < width / 2 ? "start" : "end")
.text(d => d.name)
.append("tspan")
.attr("fill-opacity", 0.7)
.text(d => ` ${d.value.toLocaleString()}`);
return svg.node();
}
width = 975
height = 720
sankey = d3.sankey()
.nodeSort(null)
.linkSort(null)
.nodeWidth(4)
.nodePadding(20)
.extent([[0, 5], [width, height - 5]])
graph = {
let index = -1;
const nodes = [];
const nodeByKey = new Map;
const indexByKey = new Map;
const links = [];
for (const k of keys) {
for (const d of data) {
const key = JSON.stringify([k, d[k]]);
if (nodeByKey.has(key)) continue;
const node = {name: d[k]};
nodes.push(node);
nodeByKey.set(key, node);
indexByKey.set(key, ++index);
}
}
for (let i = 1; i < keys.length; ++i) {
const a = keys[i - 1];
const b = keys[i];
const prefix = keys.slice(0, i + 1);
const linkByKey = new Map;
for (const d of data) {
const names = prefix.map(k => d[k]);
const key = JSON.stringify(names);
const value = d.value || 1;
let link = linkByKey.get(key);
if (link) { link.value += value; continue; }
link = {
source: indexByKey.get(JSON.stringify([a, d[a]])),
target: indexByKey.get(JSON.stringify([b, d[b]])),
names,
value
};
links.push(link);
linkByKey.set(key, link);
}
}
return {nodes, links};
}
color = d3.scaleOrdinal(["Hubei"], ["#da4f81"]).unknown("#ccc")
keys = data.columns.slice(0, -1)
data =d3.csvParse(await FileAttachment("2019-nCoV.csv").text(), d3.autoType)
d3 = require("d3@5", "d3-sankey@0.12")
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.
