md`<figure>
<img src="${await FileAttachment("20200619_170918.jpg").url()}">
</figure>`
category_array=["Sex", "Survived", "Age", "Class", "value"]
//Draw the tree here using the graphTree function. It could look simlar to that.
//graphTree(hierarchyData, {label: d => d.data.name})
//Reference: https://observablehq.com/@d3/d3-hierarchy
Tree = graphTree(hierarchyData, {label: d => d.data.name});
//Reference: https://observablehq.com/@d3/d3-hierarchy
hierarchyData = d3.hierarchy({
name: "Data",
children: children});
//Add the depth and height information to the nested data
//Reference : https://observablehq.com/@d3/d3-hierarchy
// and by learning from Emo's notebook.
children = d3.nest()
.key(d => d[category_array[0]])
.key(d => d[category_array[1]])
.key(d => d[category_array[2]])
.key(d => d[category_array[3]])
.key(d => d[category_array[4]])
.entries(data)
.map(function(group) {
return {name: group.key, children: group.values.map(function(d) {
return {name: d.key, children: d.values.map(function(o) {
return {name: o.key, children: o.values.map(function(w) {
return {name: w.key}})}})}})}})
md` The tree graph needs nested data with specific information of the nodes, this includes height and depth. Have a look at the nest and hierarchy functionalities in D3. Remember to include the functionality to alter the order of the level in the tree according to the order in category_array.`
parallelSet={
const svg = d3.create("svg").attr("viewBox", [0, 0, width, height]);
// your code
//Reference: https://observablehq.com/@john-guerra/parallel-sets
//Reference: https://observablehq.com/@lalaliy/parallel-sets
//Reference: https://observablehq.com/@cstefanache/sankey-custom-raw-data
// added the graph, snaky and colors in appandix, and axis linked with catagory_array.
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)
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")
svg.append("g")
.style("font", "10px")
.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")
return svg.node();
}
md`## Apendix`
data = d3.csvParse(await FileAttachment("titanic.csv").text(), d3.autoType)
import { table } from "@tmcw/tables/2"
dx = 12
dy = 90
treeLink = d3.linkHorizontal().x(d => d.y).y(d => d.x)
tree = d3.tree().nodeSize([dx, dy])
shape2path = require("shape2path@3")
d3 = require("d3@5", "d3-sankey@0.12")
color = d3.scaleOrdinal(d3.schemeDark2);//
sankey = d3.sankey()
.nodeSort(null)
.linkSort(null)
.nodeWidth(4)
.nodePadding(10)
.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 category_array) {
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 < category_array.length; ++i) {
const a = category_array[i - 1];
const b = category_array[i];
const prefix = category_array.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};
}
height=800
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.
