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.
Public
Edited
Jul 26, 2023
1 fork
32 stars
NC Congressional DistrictsTrivariate choropleth for racial composition in the USRacial distribution in NCWNC Zoom3D Choropleth for NC County PopulationsNC CountiesTriangulated Canadian Provinces (separate)Triangulated NC CountiesAn 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 mapGerrymandering Hexapolis by handVisualizations of gun ownership dataIncome inequality in North Carolina
Reproductive rights and ... ??
function make_map(opts = {}) {
let { max_size = 900, link_chart = null } = opts;
let map_width = width < max_size ? width : max_size;
let height = 0.575 * map_width;
let div = d3
.create("div")
.style("width", `${map_width}px`)
.style("height", `${height}px`)
.style("overflow", "hidden")
.style("position", "relative");
let svg = div
.append("svg")
.style("overflow", "hidden")
.attr("viewBox", [0, 0, map_width, height]);
let proj = d3
.geoIdentity()
.reflectY(true)
.fitSize([map_width, height], stateTiles);
let path = d3.geoPath().projection(proj);
let map = svg.append("g");
let density_map = new Map();
map
.selectAll("path.tile")
.data(stateTiles.features)
.join("path")
.attr("class", "tile")
.attr("data-fips", (o) => o.properties.fips)
.attr("data-name", (o) => o.properties.name)
.attr("data-abbr", (o) => o.properties.abbr)
.attr("data-rrs", function (d) {
let fd = data.filter((o) => o.abbr == d.properties.abbr);
if (fd.length > 0) {
return fd[0].rr_score;
} else {
return "NA";
}
})
.attr("data-covariate", function (d) {
if (covariate != "---") {
let fd = filtered_data.filter((o) => o.abbr == d.properties.abbr);
if (fd.length > 0) {
return fd[0][covariate];
} else {
return "NA";
}
}
})
.attr("d", path)
.attr("fill", (o) =>
covariate == "---"
? rr_shade(o.properties.abbr)
: state_color(o.properties.abbr)
)
.attr("stroke-width", 0.8)
.attr("stroke", "white")
.attr("stroke-linejoin", "round")
// .on("touchmove", (e) => e.preventDefault())
.on("pointerenter mouseenter", function (evt, o) {
evt.preventDefault();
if (covariate != "---") {
let class_selector = ".color" + state_color(o.properties.abbr).slice(1);
legend
.select(class_selector)
.attr("stroke", "black")
.attr("stroke-width", 2)
.raise();
if (link_chart) {
let selected_circles = d3
.select(link_chart)
.select(`#${o.properties.abbr}`)
.attr("fill", "yellow")
.attr("stroke", "black")
.attr("r", 0.005 * width)
.raise();
}
} else {
if (link_chart) {
d3.select(link_chart)
.select(`.${o.properties.abbr}`)
.attr("stroke", "black")
.attr("stroke-width", 0.002 * width)
.raise();
d3.select(link_chart).select();
}
}
})
.on("mouseout", function (evt, o) {
if (covariate != "---") {
let class_selector = ".color" + state_color(o.properties.abbr).slice(1);
legend
.select(class_selector)
.attr("stroke", "white")
.attr("stroke-width", 0.5);
if (link_chart) {
let selected_circles = d3
.select(link_chart)
.select(`#${o.properties.abbr}`)
.attr("fill", "black")
.attr("r", 0.002 * width);
}
} else {
if (link_chart) {
d3.select(link_chart)
.select(`.${o.properties.abbr}`)
.attr("stroke", null);
}
}
});
map
.selectAll("text")
.data(stateTiles.features)
.join("text")
.text((o) => o.properties.abbr)
.attr("font-size", `${0.022 * map_width}px`)
.attr("x", function (o) {
return path.centroid(o)[0];
})
.attr("text-anchor", "middle")
.attr("y", function (o) {
return path.centroid(o)[1];
})
.attr("dy", 0.008 * map_width)
.attr("pointer-events", "none");
map
.selectAll("path.tile")
.nodes()
.forEach(function (t) {
let content = html`<div>
<div style="font-weight:bold">${t.getAttribute("data-name")}</div>
<div>reproductive rights score: ${t.getAttribute("data-rrs")}</div>
${
covariate != "---"
? `<div>${covariate.replace(/_/g, " ")}: ${d3.format("0.2f")(
t.getAttribute("data-covariate")
)}</div>`
: ""
}
</div>`;
tippy(t, {
content: content,
theme: "light-border",
maxWidth: 500
});
});
let s = map_width / 10;
let legend = svg
.append("g")
.attr("transform", `translate(${map_width - 1.5 * s},${height - 1.2 * s})`);
let arrow_group = legend.append("g");
arrow_group // from http://thenewcode.com/1068/Making-Arrows-in-SVG
.append("svg:defs")
.append("marker")
.attr("id", "arrowhead")
.attr("markerWidth", 0.5 * 10)
.attr("markerHeight", 0.5 * 7)
.attr("refX", 0)
.attr("refY", 0.5 * 3.5)
.attr("orient", "auto")
.append("polygon")
// .attr("points", `0 0, 10 3.5, 0 7`);
.attr("points", `0 0, ${0.5 * 10} ${0.5 * 3.5}, 0 ${0.5 * 7}`);
let patches = legend.append("g");
let arrows = legend.append("g");
if (covariate != "---") {
let n = 5;
let dd = s / n;
let to_rr = d3
.scaleLinear()
.domain([0, n - 1])
.range([rr_scores.min, rr_scores.max]);
let to_covariate = d3
.scaleLinear()
.domain([0, n - 1])
.range([covariate_values.min, covariate_values.max]);
for (let i = 0; i < n; i++) {
for (let j = 0; j < n; j++) {
patches
.append("rect")
.attr(
"class",
"color" + color(to_rr(i), to_covariate(n - j - 1)).slice(1)
)
.attr("x", i * dd)
.attr("y", j * dd)
.attr("width", s / n)
.attr("height", s / n)
.attr("fill", color(to_rr(i), to_covariate(n - j - 1)))
.attr("stroke", "white")
.attr("stroke-width", 0.5);
}
}
arrows
.append("line")
.attr("x1", 0)
.attr("x2", s)
.attr("y1", s)
.attr("y2", s)
.attr("stroke", "black")
.attr("stroke-width", 2)
.attr("marker-end", "url(#arrowhead)");
arrows
.append("line")
.attr("x1", 0)
.attr("x2", 0)
.attr("y1", s)
.attr("y2", 0)
.attr("stroke", "black")
.attr("stroke-width", 2)
.attr("marker-end", "url(#arrowhead)");
arrows
.append("text")
.attr("x", 0.15 * s)
.attr("y", 1.2 * s)
.attr("font-size", 0.011 * width)
.text("rr-score");
arrows
.append("text")
.attr("x", -0.016 * width)
.attr("y", -0.012 * width)
.attr("font-size", 0.011 * width)
.text("covariate");
} else {
legend = Legend(
d3.scaleSequential(d3.interpolateRdBu).domain(rr_score_extent),
{
title: "rr-score",
tickFormat: ".0f"
}
);
d3.select(legend).selectAll("text").attr("font-size", "16px");
svg
.append("g")
.attr("transform", `translate(${0.3 * map_width},${0.05 * height})`)
.append("g")
.attr("transform", `scale(${max_size / 700})`)
.append(() => legend);
}
return div.node();
}
function make_chart(opts = {}) {
let { w = 900 } = opts;
let h = 0.6 * w;
let plot;
if (covariate != "---") {
let xs = filtered_data.map((o) => o.rr_score);
let xmin = d3.min(xs);
let xmax = d3.max(xs);
let xrange = xmax - xmin;
xmin = xmin - xrange / 10;
xmax = xmax + xrange / 10;
let ys = filtered_data.map((o) => o[covariate]);
let ymin = d3.min(ys);
let ymax = d3.max(ys);
let yrange = ymax - ymin;
ymin = ymin - yrange / 10;
ymax = ymax + yrange / 10;
let f = (x) => regression.coef[1] * x + regression.coef[0];
plot = Plot.plot({
width: w,
height: h,
x: { domain: [xmin, xmax] },
y: { domain: [ymin, ymax] },
marks: [
Plot.line([
[xmin + xrange / 40, f(xmin + xrange / 40)],
[xmax, f(xmax)]
]),
Plot.dot(filtered_data, {
x: "rr_score",
y: covariate,
fill: "black",
title: (o) => o.abbr,
r: 3 * Math.sqrt(width / 1152)
}),
Plot.ruleX([xmin]),
Plot.ruleY([ymin])
]
});
d3.select(plot)
.selectAll("circle")
.on("pointerenter", function () {
d3.select(this)
.attr("fill", "yellow")
.attr("stroke", "black")
.attr("r", 5 * Math.sqrt(width / 1152))
.raise();
})
.on("pointerleave", function () {
d3.select(this)
.attr("fill", "black")
.attr("r", 3 * Math.sqrt(width / 1152));
})
.nodes()
.forEach(function (c) {
let d3Circle = d3.select(c);
let value = d3Circle.select("title").text();
d3Circle.attr("id", value);
tippy(c, { content: d3Circle.attr("id"), theme: "light-border" });
d3Circle.select("title").remove();
});
} else {
plot = Plot.plot({
width: w,
height: h,
marks: [
Plot.rectY(
data,
Plot.stackY(
Plot.binX(
{ y: "count", thresholds: 7, sort: "first", title: "first" }, // title: "first",
{
x: "rr_score",
text: "abbr",
sort: "rr_score",
fill: "rr_score",
title: (d) => `${d.abbr}: RR score: ${d.rr_score}`
}
)
)
),
Plot.text(
data,
Plot.stackY(
Plot.binX(
{
y: "count",
thresholds: 7,
sort: "first",
text: "first"
// title: "first"
},
{
x: "rr_score",
sort: "rr_score",
z: "abbr",
text: "abbr",
fill: "black"
// title: (d) => `${d.name}. RR score: ${d.rr_score}`
}
)
)
),
Plot.ruleX([0]),
Plot.ruleY([0])
],
x: { ticks: 7 },
color: { scheme: "rdbu" }
});
d3.select(plot).selectAll("text").attr("pointer-events", "none");
d3.select(plot)
.selectAll("rect")
.nodes()
.forEach(function (r) {
let value = d3.select(r).select("title").text();
d3.select(r).attr("class", value.split(":")[0]);
tippy(r, {
content: value,
theme: "light-border"
});
});
d3.select(plot).selectAll("rect").select("title").remove();
}
return plot;
}
rr_shade = (abbr) =>
d3.interpolateRdBu(rr_scale(data.filter((o) => o.abbr == abbr)[0].rr_score))
rr_scale = {
let rr_scores = data.map((o) => o.rr_score);
let min = d3.min(rr_scores);
let max = d3.max(rr_scores);
return d3.scaleLinear().domain([min, max]).range([0, 1]);
}
rr_score_extent = d3.extent(data, d=>d.rr_score)
regression = {
if (covariate != "---") {
return jstat.models.ols(
filtered_data.map((o) => o[covariate]),
filtered_data.map((o) => [1, o["rr_score"]])
);
}
}
colors = [
"#d3d3d3",
"#b6cdcd",
"#97c5c5",
"#75bebe",
"#52b6b6",
"#cab6c5",
"#aeb0bf",
"#91aab9",
"#70a4b2",
"#4e9daa",
"#c098b9",
"#a593b3",
"#898ead",
"#6b89a6",
"#4a839f",
"#b77aab",
"#9e76a6",
"#8372a0",
"#666e9a",
"#476993",
"#ad5b9c",
"#955898",
"#7c5592",
"#60528d",
"#434e87"
]
function state_color(abbr) {
if (covariate != "---") {
let info = filtered_data.filter((o) => o.abbr == abbr);
if (info.length > 0) {
return color(info[0].rr_score, info[0][covariate]);
} else {
return "black";
}
} else {
return rr_shade(data.filter((o) => o.abbr == abbr));
}
}
color = (rr, cov) => colors[j(cov) + i(rr) * 5]
i = d3
.scaleQuantile()
.domain([rr_scores.min, rr_scores.max])
.range(d3.range(Math.sqrt(colors.length)))
rr_scores = {
let rr_scores = data.map((o) => o.rr_score);
rr_scores.min = d3.min(rr_scores);
rr_scores.max = d3.max(rr_scores);
return rr_scores;
}
j = d3
.scaleQuantile()
.domain([covariate_values.min, covariate_values.max])
.range(d3.range(Math.sqrt(colors.length)))
covariate_values = {
let covariate_values = filtered_data.map((o) => o[covariate]);
covariate_values.min = d3.min(covariate_values);
covariate_values.max = d3.max(covariate_values);
return covariate_values;
}
filtered_data = data.filter((o) => o[covariate] > 0)
data = FileAttachment("reproductive_rights_correlates@6.csv").csv({ typed: true })
stateTiles = {
let stateTiles = await FileAttachment("stateTiles2.json").json();
let tiles = topojson.feature(stateTiles, stateTiles.objects.tiles);
tiles.features = tiles.features.filter((o) => o.properties.abbr != "DC");
return tiles;
}
jstat = require("jstat")
tippy_style = html`<link rel="stylesheet" href="${await require.resolve(
`tippy.js/themes/light-border.css`
)}">`
tippy = require("tippy.js@6")
topojson = require("topojson-client@3")
import { Legend } from "@d3/color-legend"
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