Spike mapBubble mapChoroplethD3 U.S. Map (Live Projection)Map Maker Dot Density: Cumulative Covid CasesFIPS County Code BrushCOVID-19 Cases by CountyCMU COVIDcast API: Map makerGeoJson BoilerplateMethods of Comparison, ComparedCOVID-19: Cumulative deaths per thousand (US Counties)ChoroplethCOVID-19 in the USSanders Donation 2020 County LevelTrump Donation 2020 County LevelBiden Donation 2020 County LevelUSA County Heat MapUS County Dot MapAncestry by U.S. CountyAncestry by US County MapTry to impeach this? Challenge accepted!Streaming ShapefilesHow well does population density predict U.S. voting outcomes?Bivariate choroplethB&W Choropleth
USA County Heat Map
chart = {
const width = 960;
const height = 600;
const projection = d3.geoAlbersUsa().scale(1200).translate([width/2, height/2])
const path = d3.geoPath().projection(projection)
const svg = d3.create("svg")
.attr("viewBox", `0 0 ${width} ${height}`)
.style("width", "100%")
.style("height", "auto")
const legend = svg.append("g")
.attr("transform", "translate(600,40)")
.call(legendMaker);
const counties = svg.append("g")
.selectAll("path")
.data(topojson.feature(us, us.objects.counties).features)
.join("path")
.attr("fill", d => color(data.get(d.id)) != null ? color(data.get(d.id)) : "white")
.attr("stroke", "lightgrey")
.attr("d", path)
.append("title")
.text(d => `${data.get(d.id)}%`);
const states = svg.append("path")
.datum(topojson.mesh(us, us.objects.states))
.attr("fill", "none")
.attr("stroke", "grey")
.attr("stroke-linejoin", "round")
.attr("d", path);
return svg.node();
}
legendMaker = g => {
const x = d3.scaleLinear()
.domain(d3.extent(color.domain()))
.rangeRound([0, 260]);
g.selectAll("rect")
.data(color.range().map(d => color.invertExtent(d)))
.join("rect")
.attr("height", 8)
.attr("x", d => x(d[0]))
.attr("width", d => x(d[1]) - x(d[0]))
.attr("fill", d => color(d[0]));
g.append("text")
.attr("x", x.range()[0])
.attr("y", -6)
.attr("fill", "currentColor")
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.text("Unemployment Rate");
g.call(
d3.axisBottom(x)
.tickValues(getTickValues(color))
)
.select(".domain")
.remove();
}
schemes = [
{
name: "RdBu",
colors: [
"#e8e8e8", "#e4acac", "#c85a5a",
"#b0d5df", "#ad9ea5", "#985356",
"#64acbe", "#627f8c", "#574249"
]
},
{
name: "BuPu",
colors: [
"#e8e8e8", "#ace4e4", "#5ac8c8",
"#dfb0d6", "#a5add3", "#5698b9",
"#be64ac", "#8c62aa", "#3b4994"
]
},
{
name: "GnBu",
colors: [
"#e8e8e8", "#b5c0da", "#6c83b5",
"#b8d6be", "#90b2b3", "#567994",
"#73ae80", "#5a9178", "#2a5a5b"
]
},
{
name: "PuOr",
colors: [
"#e8e8e8", "#e4d9ac", "#c8b35a",
"#cbb8d7", "#c8ada0", "#af8e53",
"#9972af", "#976b82", "#804d36"
]
},
{
name: "W2O",
colors: [
"#2FA4DD", "#002B3F", "#F15922",
"#00C4AD", "#BFA87F", "#686060",
"#FC3C3C"
]
}
]
color = d3.scaleQuantize(extent, palette)
// color = d3.scaleLinear()
// .domain(extent )
// .range(['white', 'red'])
// .interpolate(d3.interpolate);
// ["red", "blue", "green"])
// d3.schemeReds[9])
// color = d3.scaleLinear(extent, d3.interpolateBrBG)
// ["red", "blue", "green"])
// d3.schemeReds[9])
data = new Map(dataRaw.map(i => [+i.id, +i.rate]))
extent = d3.extent([...data.values()])
// extent = [0, 10]
getTickValues = color => {
const tickValues = color.range().map(d => color.invertExtent(d)[0])
const lastColor = color.range().slice(-1)[0]
const lastTick = color.invertExtent(lastColor)[1]
tickValues.push(lastTick)
return tickValues
}
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