chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
svg.append(legend)
.attr("transform", "translate(670,200)");
svg.append("g")
.selectAll("path")
.data(topojson.feature(polygons, polygons.objects.NJCounties).features)
.join("path")
.attr("fill", d => color(data.get(d.properties[idAttribute])))
.attr("stroke", "black")
.attr("d", path)
.append("title")
.text(d => `${d.properties[idAttribute]}, ${format(data.get(d.properties[idAttribute]))}`);
return svg.node();
}
labels = ["low", "med", "high"]
n = Math.floor(Math.sqrt(colors.length))
x = d3.scaleQuantile(Array.from(data.values(), d => d[0]), d3.range(n))
y = d3.scaleQuantile(Array.from(data.values(), d => d[1]), d3.range(n))
path = d3.geoPath().projection(projection)
//Rotate the map sets the longitude of origin for our UTM projection.
projection = d3.geoTransverseMercator().rotate([87,0]).fitExtent([[10, 10], [width, height]], polygon_features);
polygon_features = topojson.feature(polygons, polygons.objects.NJCounties)
data = Object.assign(new Map(d3.csvParse(await FileAttachment("NJpopDenNumSites.csv").text(), ({COUNTY, SQ_MILES, POP2010, NUMSITES}) => [COUNTY, [POP2010/SQ_MILES, NUMSITES]])), {title: ["Pop Density", "Contaminated Sites"]})
idAttribute = "COUNTY"
formatNum = d3.format(".1f")
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.
