Building and Using Tools to See.
UVA Architecture + Data Science. IT Director. Instructor.
<svg width="1000" height="500">
<style>
#usstates path {fill: #eee; stroke: #ddd; opacity: 0.5;}
</style>
<g id="usstates"></g> <!-- a layer for the map base -->
<g id="rings"></g> <!-- a layer for the gap rings -->
</svg>
map = d3.select(mapContainer) // d3 select the container object and/or layer to draw into
projection = d3.geoAlbers() // set map projection
import {basemaps, drawMapLayer, geoCentroids} with {projection} from "@emfielduva/dvlib_maps" // import library functions
usstates = (await(basemaps.us_states20m.geojson).json()) // get the states basemap from my collection.
mapLayers = {
let mapLayers = []; // collection of layers
mapLayers["usstates"] = drawMapLayer(map,"usstates",usstates.features,"properties.NAME"); // draw the base layer
return mapLayers; // return them for use later
}
usstateCentroids = {
let usstateCentroids = geoCentroids(usstates.features, "properties.NAME");
usstateCentroids.forEach(d => {
d.lon = d.coord[0];
d.lat = d.coord[1];
});
return usstateCentroids;
}
data = FileAttachment("covid19_vaccinations_in_the_united_states@1.csv").csv()
data.forEach(d => d.population = +d["Residents with at least one dose"] * 100 / +d["Percent of total pop with at least one dose"])
mapLayers["rings"] = map.select("#rings")
.selectAll("g")
.data(usstateCentroids)
.join("g")
.each((d,i,nodes) => {
let nodeElem = d3.select(nodes[i]);
let location = projection([d.lon,d.lat]);
let svgCoords = location[0] + "," + location[1];
nodeElem.attr("transform", "translate(" + svgCoords + ")");
nodeElem.attr("id", (d,i) => "ring"+i);
if (d.name == "New York") {d.name = "New York State"} // handle naming exception in the data.
let dataThisState = data.find(s => s["Jurisdiction (State/Territory) or Federal Entity"] == d.name);
let rScale = .01;
let innerRad = rFromArea(dataThisState["Residents with a completed primary series"]) * rScale;
let outerRad = rFromArea(dataThisState["population"]) * rScale;
dvRing(nodeElem,outerRad,innerRad);
})
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.