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.
A unimodal function with fractal level curvesA long scrollable PlotWavy spheresTwo line chartsFidding with axes labelsJumpy bar plotCopying from one SVG to anotherRegression mark with legendAdding data to array and plot histogram after each added data pointLegends and Swatches in SVGDrawing the MNIST digitsDelayed evaluationSmooth Zooming with imagesForce directed fit and zoomStatic ColorsReproduce a Gantt chartSpecifying months in a PlotCircular octa-gasketExtracting SVGProblem with domain when using group?d3 cubic bezier curveWorld population bubble mapMutliple bubble maps for CSV dataViewing a grid of images via FileAttachment.zip()Plotting a few points on a mapDisplaying Folium maps in iframesTextured globeAn SVG from an embedded cellAges of US SenatorsCovid Data Source Scatter PlotA dot plot with datesAttaching a pointerenter event to the lines in a chart
Highlight neighbors
map = {
let svg = d3.create("svg").attr("width", w).attr("height", h);
let map = svg.append("g").attr("id", "map");
let path = d3.geoPath().projection(projection);
map
.selectAll("path")
.data(contiguous_states.features)
.join("path")
.attr("d", path)
.attr("fill", "white")
.attr("stroke", "black")
.attr("stroke-width", 2);
let nodes = contiguous_states.features.map(function (o, id) {
let [x0, y0] = projection([o.properties.longitude, o.properties.latitude]);
return {
id: o.properties.postal,
neighbors: o.properties.neighbors,
x: x0,
y: y0
};
});
let link = svg.append("g").attr("class", "links");
link
.selectAll("line")
.data(state_adjacencies)
.join("line")
.attr("x1", (d) => d.x1)
.attr("y1", (d) => d.y1)
.attr("x2", (d) => d.x2)
.attr("y2", (d) => d.y2)
.attr("class", (d) => `${d.source} ${d.target}`)
.attr("stroke-width", 0.1)
.attr("stroke", "black");
let node = svg.append("g");
node
.selectAll("circle")
.data(nodes)
.join("circle")
.attr("id", function (d) {
return d.id;
})
.attr("r", 5)
.attr("fill", "black")
.attr("cx", (d) => d.x)
.attr("cy", (d) => d.y)
.on("pointerenter", function (_, n) {
d3.select(this).attr("fill", "green");
let state = n.id;
link.selectAll(`.${state}`).attr("stroke-width", 2);
n.neighbors.forEach(function (i) {
node
.selectAll(`#${contiguous_states.features[i].properties.postal}`)
.attr("fill", "red");
});
})
.on("pointerleave", function () {
link.selectAll("line").attr("stroke-width", 0.1);
node.selectAll("circle").attr("fill", "black");
});
return svg.node();
}
projection = d3.geoAlbers().fitSize([w - 10, h], contiguous_states)
h = 0.625 * w
w = d3.min([width, 1000])
contiguous_states = {
let contiguous_states = await (
await FileAttachment("contiguous_states3.json")
).json();
contiguous_states.objects.contiguous_states.geometries =
contiguous_states.objects.contiguous_states.geometries.filter(
(o) => o.properties.postal != "DC"
);
let adjacency_lists = topojson.neighbors(
contiguous_states.objects.contiguous_states.geometries
);
contiguous_states = topojson.feature(
contiguous_states,
contiguous_states.objects.contiguous_states
);
contiguous_states.features.forEach(function (o, i) {
o.properties.neighbors = adjacency_lists[i];
});
return contiguous_states;
}
state_adjacencies = {
let properties = contiguous_states.features.map((o) => o.properties);
let adjacency_indices = contiguous_states.features
.map((o, i) => o.properties.neighbors.map((j) => [i, j]))
.flat()
.filter((a) => a[0] < a[1]);
adjacency_indices = adjacency_indices.map(function (a) {
let [x1, y1] = projection([
properties[a[0]].longitude,
properties[a[0]].latitude
]);
let [x2, y2] = projection([
properties[a[1]].longitude,
properties[a[1]].latitude
]);
return {
source: properties[a[0]].postal,
target: properties[a[1]].postal,
x1,
x2,
y1,
y2
};
});
return adjacency_indices;
}
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.
