I love to build dataviz for insight discovery. I also love to put technology to the service of humanity
chart = {
// Specify the dimensions of the chart.
const width = 928;
const height = 600;
// Specify the color scale.
const color = d3.scaleOrdinal(d3.schemeCategory10);
const w = d3.scaleLinear().domain([0, d3.max(data.links, l => l.value)]).range([0.1, 3]);
// ✅ We compute the autofit by using scales for x and y
const x = d3.scaleLinear().range([0, width]);
const y = d3.scaleLinear().range([0, height]);
// The force simulation mutates links and nodes, so create a copy
// so that re-evaluating this cell produces the same result.
const links = data.links.map((d) => ({ ...d }));
const nodes = data.nodes.map((d) => ({ ...d }));
// Create a simulation with several forces.
const simulation = d3
.forceSimulation(nodes)
.force(
"link",
d3.forceLink(links).id((d) => d.id)
)
.force("charge", d3.forceManyBody())
.force("center", d3.forceCenter(width / 2, height / 2))
.on("tick", ticked);
// Create the SVG container.
const svg = d3
.create("svg")
.attr("width", width)
.attr("height", height)
.attr("viewBox", [0, 0, width, height])
.attr("style", "max-width: 100%; height: auto;");
// Add a line for each link, and a circle for each node.
const link = svg
.append("g")
.attr("stroke", "#bbb")
.attr("stroke-opacity", 0.6)
.selectAll()
.data(links)
.join("line")
.attr("stroke-width", (d) => w(d.value));
const node = svg
.append("g")
.attr("stroke", "#fff")
.attr("stroke-width", 1.5)
.selectAll()
.data(nodes)
.join("circle")
.attr("r", 3.5)
.attr("fill", (d) => color(d.cluster));
node.append("title").text((d) => d.id);
// Add a drag behavior.
node.call(
d3.drag().on("start", dragstarted).on("drag", dragged).on("end", dragended)
);
// Set the position attributes of links and nodes each time the simulation ticks.
function ticked() {
// ✅ Adjust the domain of the autofit scales
if (autoFit) {
x.domain(d3.extent(nodes, (d) => d.x)).nice();
y.domain(d3.extent(nodes, (d) => d.y)).nice();
} else {
x.domain([0, width]);
y.domain([0, height]);
}
link
.attr("x1", (d) => x(d.source.x))
.attr("y1", (d) => y(d.source.y))
.attr("x2", (d) => x(d.target.x))
.attr("y2", (d) => y(d.target.y));
node.attr("cx", (d) => x(d.x)).attr("cy", (d) => y(d.y));
}
// Reheat the simulation when drag starts, and fix the subject position.
function dragstarted(event) {
if (!event.active) simulation.alphaTarget(0.3).restart();
event.subject.fx = event.subject.x;
event.subject.fy = event.subject.y;
}
// Update the subject (dragged node) position during drag.
function dragged(event) {
event.subject.fx = event.x;
event.subject.fy = event.y;
}
// Restore the target alpha so the simulation cools after dragging ends.
// Unfix the subject position now that it’s no longer being dragged.
function dragended(event) {
if (!event.active) simulation.alphaTarget(0);
event.subject.fx = null;
event.subject.fy = null;
}
// When this cell is re-run, stop the previous simulation. (This doesn’t
// really matter since the target alpha is zero and the simulation will
// stop naturally, but it’s a good practice.)
invalidation.then(() => simulation.stop());
return svg.node();
}
data = datasetSelected.data
coAuthorshipNetwork = FileAttachment("coauthorshipNetwork2023_full.json")
.json()
.then((res) => {
res.nodes = res.nodes.map((d, i) => ((d.id = i), d));
return res;
})
senateNetwork = ({
nodes: filteredNodes.map((d) => {
d.id = d.member_full;
d.cluster = d.party;
return d;
}),
links: filteredLinks
})
import {filteredNodes, filteredLinks} from "@john-guerra/us-senate-network"
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