height = 610
width = 975
path_points = d3.geoPath().projection(projection)
path_basemap = d3.geoPath().projection(projection)
projection = d3.geoAlbers()
format = d3.format(".2s")
//proportional symbols
radius = d3.scaleSqrt([0, d3.max(attribute)], [0, 30])
//radius = d3.scaleThreshold()
//.domain(naturalbreaks)
//.range(radiusArray)
sizeArrayForLegend = Array.from(radiusArray, d=>Math.PI*Math.pow(d, 2))
radiusArray = [3, 9, 23, 40]
circleLabels = Array.from(naturalbreaks, d=> format(Math.pow(d, 2)))
colors = d3.scaleThreshold()
.domain(naturalbreaks)
.range(YlOrRd)
YlOrRd = ["#ffffb2", "#fecc5c", "#fd8d3c", "#e31a1c"]
naturalbreaks = simple.ckmeans(attribute, 4).map(v => v.pop())
d3.max(attribute)
attribute = Array.from(csv_data.values(), d => d[1])
//attribute = Array.from(csv_data, d=>Math.sqrt(d.properties[attributeName]))
attributeName = "CombinedRate"
idName = "STATE_FIPS"
//import the point data (geojson)
points = FileAttachment("allstates_points.geojson").json()
csv_data = d3.csvParse(await FileAttachment("State-and-Local-Sales-Tax-Rates-2022@2.csv").text(), ({FIPS, CombinedRate}) => [+FIPS, +CombinedRate])
data = Object.assign(new Map(csv_data))
//import the polygon base map data
basepolygons = FileAttachment("allstates@1.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.
