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.
NC Congressional DistrictsTrivariate choropleth for racial composition in the USRacial distribution in NCWNC Zoom3D Choropleth for NC County PopulationsNC CountiesTriangulated Canadian Provinces (separate)An X3D GlobeCanadian Elections 3DWNC SurroundElectoral Results TilegramThe new Electoral CollegeElectoral MapGPX rides with Leaflet and OSMOld encoded polyline rides with LeafletGPX rides with Maplibre and MaptilerBuncombe county votingThe NC Congressional redistricting battleHexapolis 538Zillow Home PricesSetting up HexapolisCOVID curvesThirty day Map Challenge - Day 1Simple grid cartogram2020 Census Apportionment TilegramMass shootings in the USHBCUsNC State Legislative Elections 2022Hierarchical Structure of the US RegionsIndigenous territories of the SoutheastD3.force to desired positionPopulation Choropleth for the Contiguous US StatesPlotting a few points on a mapMutliple bubble maps for CSV dataWorld population bubble mapReproductive rights and ... ??Gerrymandering Hexapolis by handVisualizations of gun ownership dataIncome inequality in North Carolina
Triangulated NC Counties
svg = {
let svg_width = width;
let svg_height = 0.4 * svg_width;
let svg = d3
.create('svg')
.attr('width', svg_width)
.attr('height', svg_height);
let x_scale = d3
.scaleLinear()
.domain([bounds.xmin, bounds.xmax])
.range([0, svg_width]);
let y_scale = d3
.scaleLinear()
.domain([bounds.ymin, bounds.ymax])
.range([svg_height, 0]);
let pts_to_path = d3
.line()
.x(function(d) {
return x_scale(d[0]);
})
.y(function(d) {
return y_scale(d[1]);
});
let triangles = triangulated_counties
.map(c => extract_geometry(c, 'triangle'))
.flat(1);
svg
.selectAll('path.tri')
.data(triangles)
.enter()
.append("path")
.attr('class', 'tri')
.attr('d', function(d) {
// console.log(d);
return pts_to_path(d);
})
.attr("stroke", "black")
.attr("stroke-width", .1)
.attr('fill', 'white');
let segments = triangulated_counties
.map(c => extract_geometry(c, 'segment'))
.flat(1);
svg
.selectAll('path.seg')
.data(segments)
.enter()
.append("path")
.attr('class', 'seg')
.attr('d', function(d) {
console.log(['seg', d]);
return pts_to_path(d);
})
.attr("stroke", "black")
.attr("stroke-width", 2)
.attr('fill', 'white');
return svg.node();
}
triangulated_counties.map(c => extract_geometry(c, 'segment')).flat(1)
bounds = {
let xpts = triangulated_counties.map(c => c.pts.map(xy => xy[0])).flat();
let ypts = triangulated_counties.map(c => c.pts.map(xy => xy[1])).flat();
let xmin = d3.min(xpts);
let xmax = d3.max(xpts);
let ymin = d3.min(ypts);
let ymax = d3.max(ypts);
return { xmin: xmin, ymin: ymin, xmax: xmax, ymax: ymax };
}
extract_geometry(triangulated_counties[0], 'triangle')
//triangulated_counties.map(c => extract_geometry(c, 'triangle')).flat(2)
function extract_geometry(county, type) {
let pts = county.pts;
let geo;
if (type == 'triangle') {
geo = county.triangles;
} else if (type == 'segment') {
geo = county.segments;
}
return geo.map(function(indices) {
return indices.map(i => pts[i]);
});
}
triangulated_counties = FileAttachment('nc_triangulated3.json').json()
d3 = require('d3@5')
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.