data1 = FileAttachment("Viz1.csv").csv({typed: true})
links = d3.csvParse(await FileAttachment("Dh150 Final Project - v_3.csv").text())
types = Array.from(new Set(links.map(d => d.type)))
data = ({nodes: Array.from(new Set(links.flatMap(l => [l.source, l.target])), id => ({id})), links})
height = 1000
color = d3.scaleOrdinal(types, d3.schemeCategory10)
function linkArc(d) {
const r = Math.hypot(d.target.x - d.source.x, d.target.y - d.source.y);
return `
M${d.source.x},${d.source.y}
A${r},${r} 0 0,1 ${d.target.x},${d.target.y}
`;
}
drag = simulation => {
function dragstarted(event, d) {
if (!event.active) simulation.alphaTarget(0.3).restart();
d.fx = d.x;
d.fy = d.y;
}
function dragged(event, d) {
d.fx = event.x;
d.fy = event.y;
}
function dragended(event, d) {
if (!event.active) simulation.alphaTarget(0);
d.fx = null;
d.fy = null;
}
return d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended);
}
d3 = require("d3@6")
import {swatches} from "@d3/color-legend"
/*
SPARQL QUERY
SELECT ?hospitalLabel ?cityLabel ?hospital ?city
WHERE {
?hospital wdt:P31 wd:Q16917.
?hospital wdt:P17 wd:Q30.
?hospital wdt:P131 ?city.
SERVICE wikibase:label { bd:serviceParam wikibase:language "[AUTO_LANGUAGE],en" }
}
*/
hospitals = FileAttachment("Dh150 Final Project - Viz2 (1).csv").csv({typed: true})
namemap = new Map(us.objects.states.geometries.map(d => [d.properties.name, d.id]))
us = FileAttachment("counties-albers-10m.json").json()
import {Legend} from "@d3/color-legend"
valuemap = new Map(hospitals.map(d => [d.name, d.rate]))
/*
SPARQL QUERY
SELECT ?disease ?doid ?enLabel (count(?language) as ?languages)
WHERE
{
?disease wdt:P699 ?doid ;
rdfs:label ?label ;
rdfs:label ?enLabel .
FILTER (lang(?enLabel) = "en")
BIND (lang(?label) AS ?language)
}
GROUP BY ?disease ?doid ?enLabel
ORDER BY desc(?languages)
LIMIT 1000
*/
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.