EJ Fox & Ian Johnson
streaming data, code, acid, design
Coding With Fire - Crowd Control Color PaletteCMU COVIDcast APICMU COVIDcast API: Map makerMap Maker Dot Density: Cumulative Covid CasesPattern Moire - Line & Circle Grids with ColorschemesPattern Moire - Line & Circle GridsCustom Cluster Force LayoutCMU COVIDcast API: Map maker Bubbles CanvasCMU COVIDcast API: Map maker BubblesCMU COVIDcast API: Map maker Bubbles IICMU COVIDcast API: Map maker TimelapseCoding With Fire: Mind MapGraphene MoiréGraphene Moiré FirebaseGraphene Moiré 3DCoding With Fire: Paths as PointsCoding With Fire: 3D PathsFreaky Dot PatternsCoding With Fire: NYPD CCRBWhere are votes at risk?Voronoi PurpleAirDeadline Timers 2CMU COVIDcast API: Bubbles ExportEmojisEmoji Treemap Small MultiplesCounties with DatasetteAmerican Community Survey 2018 by CountyRegistered Voters by County 2016-2018Registered Voters by County 2016-2018: Bubble LinesCMU COVIDcast API: Bubbles Dark ModeUS Bubble Choropleth: Travel From CentroidUS Bubble Choropleth: Travel From CentroidCMU COVIDcast API: Bubbles Textures Interactive TimelapseChoropleth with Textures.jsForce Bubble Map with Textures.jsWhere Are Votes Outstanding? (Data Simulation)Where Are Votes Outstanding? Visualization IdeasElectoral College Unit ChartsElectoral College Unit Charts With TextElectoral College Unit Shuffle
Population Change by County 2016-2018: Bubble Lines
Also listed in…
Election Explorations
countySVG
projection = d3.geoAlbersUsa().fitSize([width - 20, height - 30], countyShapes)
rPopScale = d3
.scaleSqrt()
.domain(populationExtent)
.range([1, 22])
diffScale = {
let max = Math.max(Math.abs(diffExtent[0]), diffExtent[1]);
return d3
.scaleDiverging()
.domain([-max, 0, max])
.range([-500, 0, 500]);
}
diffOpacity = {
let max = Math.max(Math.abs(diffExtent[0]), diffExtent[1]);
return d =>
d3
.scaleDiverging()
.domain([-max, 0, max])
.range([.6, 0, .6])(d) + 0.25;
}
diffColor = {
return d3
.scaleDiverging()
.domain([diffExtent[0], 0, diffExtent[1]])
.range(["orange", "white", "teal"]);
}
// diff = diffRegister
diff = diffPopulation
diffRegister = d => {
let c = eavsByCounty.get(d.id)
if(!c) return 0;
return +c["A1a|2018"] - +c["A1a|2016"];
}
diffPopulation = d => {
let d2018 = demographicsData[2018].get(d.id);
let d2016 = demographicsData[2016].get(d.id);
if (!d2018 || !d2018) return 0;
return +d2018["B01003_001E"] - +d2016["B01003_001E"];
}
turf.centroid(countyShapes.features[0])
center = d => {
return projection(turf.centroid(d).geometry.coordinates) || [0, 0];
}
allYearsFlat = FileAttachment("allYearsFlat@1.csv").csv({ typed: false })
allYearsFlat.filter(d => d.State_Full == "WISCONSIN")
allYearsFlat.filter(d => diff(d) < -1000000)
populationExtent = d3.extent(countyShapes.features, d => {
let c = demographicsData[2018].get(d.id);
if (c) return c["B01003_001E"];
return 0;
})
circles = {
let localNodes = countyShapes.features
.map(d => {
let e = eavsByCounty.get(d.id);
let c = center(d);
let demo = demographicsData[2018].get(d.id);
let pop = demo ? demo["B01003_001E"] : 0;
let o = {
...d,
cx: c[0],
cy: c[1],
x: c[0],
y: c[1]
};
if (e) {
o.p = rPopScale(pop);
o.value = diff(e);
}
return o;
})
.filter(d => !isNaN(d.p));
// console.log(localNodes);
let simulation = d3
.forceSimulation(localNodes)
.force(
"collide",
d3
.forceCollide()
// .radius(d => d.p) // for spacing by population
.radius(d => d.p + 1) // for spacing by metric
.strength(1)
)
.force(
"x",
d3.forceX(d => {
return d.cx;
})
)
.force(
"y",
d3.forceY(d => {
return d.cy;
})
);
simulation.tick(100);
localNodes.sort((a, b) => a.metric - b.metric);
return localNodes;
}
eavsByCounty = new Map(
allYearsFlat.map(d => {
let s = String(d.FIPSCode);
return [s.slice(0, s.length - 5).padStart(5, "0"), d];
})
)
diffExtent = d3.extent(countyShapes.features, diff)
d3.min(countyShapes.features, diff)
import { legend } from "@d3/color-legend"
fips = countySVG ? countySVG.id : ""
eav = eavsByCounty.get(fips)
eav ? diff(countySVG) : ""
height = 700
pop2016 = demographicsData[2016].get(fips)["B01003_001E"]
pop2018 = demographicsData[2018].get(fips)["B01003_001E"]
format = d3.format(",d")
import {
demographicsData,
selectedFields,
niceLabel,
countyShapes
} from "@enjalot/us-county-datasets"
d3 = require("d3@6")
(d3.selection.prototype.moveToFront = function() {
return this.each(function() {
this.parentNode.appendChild(this);
});
})
FileAttachment("keyLables.json").json()
turf = require('https://bundle.run/turf@3.0.14')
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