I'm a professor of mathematics at the University of North Carolina Asheville. I've also done a fair amount of consulting work over the years focusing on scientific and data visualization.
I'm happy to be part of the first Observable Ambassador's cohort.
Published
Edited
Jun 26, 2021
22 stars
// The main function
function make_map() {
let height = 0.4 * width;
let div = d3
.create("div")
.style("width", `${width}px`)
.style("height", `${height}px`)
.style("overflow", "hidden");
let svg = div
.append("svg")
.style("width", `${width}px`)
.style("height", `${height}px`)
.style("overflow", "hidden")
.style("background", "white");
// The map data is preprojected Albers Equal area for NC
let proj = d3
.geoIdentity()
.reflectY(true)
.fitSize([width, height], map_data.tracts);
let path = d3.geoPath().projection(proj);
let map = svg.append("g");
let tracts = map
.append("g")
.selectAll("path.tract")
.data(map_data.tracts.features)
.join("path")
.attr("d", path)
.attr("class", "tract")
.attr("id", (d, i) => `tract${i}`)
.attr("data-geoid", (d) => d.properties.GEOID)
.style("fill", function (d) {
return color_map.get(d.properties.GEOID);
})
.style("stroke-width", "0.2px")
.style("stroke-opacity", 0.2)
.style("stroke", "#000")
.style("stroke-linejoin", "round");
tracts
.on("mouseenter", function () {
d3.select(this).style("stroke-width", "1px").style("stroke-opacity", 1);
})
.on("mouseleave", function () {
d3.select(this)
.style("stroke-width", "0.2px")
.style("stroke-opacity", 0.2);
});
tracts.nodes().forEach((c) => {
tippy(c, {
allowHTML: true,
maxWidth: 420,
theme: "light",
content: table_map.get(c.getAttribute("data-geoid"))
});
});
let cities = map.append("g");
let city_names = cities
.selectAll("text.city")
.data(city_data)
.join("text")
.attr("class", "city")
.attr("x", (d) => proj([d.x, d.y])[0])
.attr("y", (d) => proj([d.x, d.y])[1])
.text((d) => d.city)
.style("font-family", "sans-serif")
.style("font-size", "14px")
.attr("pointer-events", "none");
let city_markers = cities
.selectAll("circle.city")
.data(city_data)
.join("circle")
.attr("class", "city")
.attr("cx", (d) => proj([d.x, d.y])[0])
.attr("cy", (d) => proj([d.x, d.y])[1])
.attr("r", 3)
.style("fill", "yellow")
.attr("pointer-events", "none");
svg.call(
d3
.zoom()
.extent([
[0, 0],
[width, height]
])
.translateExtent([
[0, 0],
[width, height]
])
.scaleExtent([1, 8])
.duration(750)
.on("zoom", function (evt) {
map.attr("transform", evt.transform);
map.selectAll(".highlight").remove();
// map
// .selectAll("path.tract")
// .style("stroke-width", `${0.2 / d3.event.transform.k}px`);
map.selectAll("circle.city").attr("r", `${3 / evt.transform.k}`);
map
.selectAll("text.city")
.style("font-size", `${14 / evt.transform.k ** 0.75}px`);
})
);
return div.node();
}
// The population data comes from the most recent five year
// American Community Survey estimates, which is 2018:
// https://www.census.gov/data/developers/data-sets/acs-5year.html
// https://api.census.gov/data/2018/acs/acs5/groups/B02001.html
raw_data = (await (await fetch(
'https://api.census.gov/data/2018/acs/acs5?get=NAME,B02001_001E,B02001_002E,B02001_003E&for=tract:*&in=state:37'
)).json()).slice(1)
// This map associates an HTML table with each tract GEOID
// to be shown as a tooltip.
table_map = {
let table_map = new Map();
raw_data.forEach(function([
place,
total,
white,
black,
state_fips,
county_fips,
tract_id
]) {
let div = d3.create('div');
let [tract, county, state] = place.split(', ');
tract = tract.slice(7);
div.append('h3').text(`${tract} in ${county}`);
//.style('color', 'white');
let table = div.append('table');
let head = table.append('thead').append('tr');
head.append('th').text('Race');
head.append('th').text('Population');
head.append('th').text('Percentage');
let combined_row = table.append('tr');
combined_row.append('td').text('All');
combined_row.append('td').text(`${total}`);
let white_row = table.append('tr');
white_row.append('td').text('White');
white_row.append('td').text(`${white}`);
white_row.append('td').text(`${d3.format('0.2f')((100 * white) / total)}%`);
let black_row = table.append('tr');
black_row.append('td').text('Black');
black_row.append('td').text(`${black}`);
black_row.append('td').text(`${d3.format('0.2f')((100 * black) / total)}%`);
let other_row = table.append('tr');
other_row.append('td').text('Other');
other_row.append('td').text(`${total - white - black}`);
other_row
.append('td')
.text(`${d3.format('0.2f')((100 * (total - white - black)) / total)}%`);
table_map.set(state_fips + county_fips + tract_id, div.node().innerHTML);
});
return table_map;
}
// Associate a color with each tract GEOID.
color_map = {
let color_map = new Map();
let max = d3.max(raw_data.map(o => parseFloat(o[1])));
raw_data.forEach(function([
place,
total,
white,
black,
state_fips,
county_fips,
tract_id
]) {
let geoid = state_fips + county_fips + tract_id;
if (total > 0) {
let population_density = density_map.get(geoid);
color_map.set(
geoid,
`rgba(${(255 * white) / total}, ${(255 * black) / total}, ${(255 *
(total - white - black)) /
total}, ${Math.pow(population_density / density_map.max, 0.25)})`
);
} else {
color_map.set(geoid, '#eee');
}
});
return color_map;
}
density_map = {
let density_map = new Map();
map_data.tracts.features
.map(c => c.properties)
.forEach(function(o) {
let geoid = o.GEOID;
let pop = pop_map.get(geoid).total;
let density = pop / o.ALAND;
density_map.set(geoid, density);
});
density_map.max = d3.max(Array.from(density_map.values()));
return density_map;
}
pop_map = {
let pop_map = new Map();
raw_data.forEach(function(o) {
pop_map.set(o[4] + o[5] + o[6], { total: o[1], white: o[2], black: o[3] });
});
return pop_map;
}
// Load the TopoJSON map file
map_data = {
let map_file = await FileAttachment("nc_tracts_topo.json").json();
let nc_tracts = topojson.feature(map_file, map_file.objects.nc_tracts);
return {
tracts: nc_tracts
};
}
// Display just a few cities
city_data = d3.csvParse(`city,lat,lon,x,y
Asheville,35.6,-82.55,-243640,3758538
Charlotte,35.2271,-80.8431,-89404,3714312
Durham,35.994,-78.8986,86782,3799379
Fayetteville,35.0527,-78.8784,89635,3694965
Raleigh,35.7796,-78.6382,110555,3775851
Wilmington,34.2104,-77.886,182013,3602891
Winston-Salem,36.0999,-80.2442,-34513,3810776`)
// tippy = require("https://unpkg.com/tippy.js@2.5.4/dist/tippy.all.min.js")
tippy = require("tippy.js@6")
topojson = require("topojson-client@3")
d3 = require('d3-selection@2', 'd3-array@2', 'd3-format@2', 'd3-geo@2', 'd3-zoom@2', 'd3-dsv@2')
tippy_style = html`<link rel="stylesheet" href="${await require.resolve(
`tippy.js/themes/light.css`
)}">`
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.
