Published
Edited
Apr 28, 2020
Insert cell
md`# Choropleth Mapping [GEOG 3540]
Median Age in Iowa Counties, Source: [Census 2010]`
Insert cell
d3 = require("d3@5")
Insert cell
import {legend} from "@d3/color-legend"
Insert cell
format = d => `${d}%`
Insert cell
topojson = require("topojson-client@3")
Insert cell
iowa = FileAttachment("iowa_counties_topo.json").json()
Insert cell
counties = topojson.feature(iowa, iowa.objects.iowa_counties)
Insert cell
csv_data = d3.csvParse(await FileAttachment("iowa_counties.csv").text(),({FIPS, MED_AGE}) => [FIPS, [+MED_AGE]])
Insert cell
data = Object.assign(new Map(csv_data), {title: "Median Age"})
Insert cell
med_age = Array.from(csv_data.values(), d => d[1][0])
Insert cell
//more information on sequential scales: https://observablehq.com/@d3/sequential-scales
// color = d3.scaleSequentialQuantile([...data.values()], d3.interpolateBlues)
//quantile classification:
color = d3.scaleQuantile()
.domain(med_age) // pass the whole dataset to a scaleQuantile’s domain
.range([d3.color("#a1dab4"), d3.color("#41b6c4"), d3.color("#2c7fb8"),d3.color("#253494")])
Insert cell
width = 975
Insert cell
height = 610
Insert cell
//Rotate the map sets the longitude of origin for our Albers projection.
projection = d3.geoTransverseMercator().rotate([94,0]).fitExtent([[80, 80], [width, height]], counties);
//d3 reference for projections: https://github.com/d3/d3-geo/blob/master/README.md

//use the following url for specific projection settings: https://github.com/veltman/d3-stateplane
//Use this code to set up the map projection (if different than geographic projection)
//projection = d3.geoMercator().fitExtent([[margin, margin], [width - margin, height - margin]], counties)
Insert cell
//Using a path generator to project geometry onto the map
path = d3.geoPath().projection(projection);
Insert cell
chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);

// svg.append("g")
// .attr("transform", "translate(360,20)")
// .append(() => legend({color, title: data.title, width: 260, tickFormat: ".1f"}));
svg.append("g")
.attr("transform", "translate(360,20)")
.append(() =>
legend({
color: color,
title: data.title,
tickFormat: ".1f"
})
);

svg.append("g")
.selectAll("path")
.data(counties.features)
.join("path")
.attr("stroke", "white")
.attr("stroke-linejoin", "round")
.attr("fill", d => color(data.get(d.properties.FIPS)[0]))
.attr("d", path)
.append("title")
.text(d => " Median Age: " + data.get(d.properties.FIPS));

return svg.node();
}
Insert cell

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.
Learn more