height = 610
width = 975
path_points = d3.geoPath().projection(projection)
path_basemap = d3.geoPath().projection(projection)
projection = d3.geoAlbers()
// Set up the projection centered on Iowa
.center([0, 42.0]) // latitude center
.rotate([93.5, 0]) // longitude center (Iowa is ~93.5°W)
.parallels([29.5, 45.5]) // standard parallels for conic projections
.scale(8000) // zoom level; adjust depending on canvas size
.translate([width / 2, height / 2]) // center it in your SVG
format = d3.format(".2s")
//proportional symbols
//radius = d3.scaleSqrt([0, d3.max(attribute)], [0, 30])
radius = d3.scaleThreshold()
.domain(attribute)
.range(radiusArray)
sizeArrayForLegend = Array.from(radiusArray, d=>Math.PI*Math.pow(d, 2))
radiusArray = [3, 6, 12, 20]
circleLabels = Array.from(cluster, d=> format(Math.pow(d, 2)))
quantiles = d3.scaleQuantile()
.domain(attribute)
.range(pinks)
pinks = ["#feebe2", "#fbb4b9", "#f768a1", "#ae017e"]
cluster = simple.ckmeans(attribute, 4).map(v => v.pop())
d3.max(attribute)
attribute = Array.from(points.features, d=>Math.sqrt(d.properties[attributeName]))
attributeName = "T_Respiratory_Disease_Death_Data___Resp_Crude"
idName = "FIPS"
//import the point data (geojson)
points = FileAttachment("CAFOResp.geojson").json()
//import the polygon base map data
basepolygons = FileAttachment("iowa_counties_topo.json").json()
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.
