// CHEAT SHEET IN COMMENTS
//Data is displayed when hovering over polygons with the FIPS, both variable values and the classification(low, medium, high) next to the variable
chart = {
const svg = d3.create("svg")
//enlarged viewbox with 10,10 to create a margin of 10
.attr("viewBox", [10, 10, width, height]);
//Creates Legend and placement is in the translate function
svg.append(legend)
.attr("transform", "translate(690,90)");
//fills map with colors from feature
svg.append("g")
.selectAll("path")
.data(topojson.feature(tracts, tracts.objects.ia_covid19_county).features)
.join("path")
//Fills base geometries with the data from CSV
.attr("fill", d => color(data.get(d.properties.FIPS)))
.attr("d", path)
.append("title")
.text(d => `${d.properties.FIPS}, ${format(data.get(d.properties.FIPS))}`)
.attr("fill", d => color(data.get(d.properties.NAME)))
.attr("d", path)
.append("title")
.text(d => " Yield: " + data.get(d.properties.NAME));
svg.selectAll(".subunit-label")
.data(ctracts.features)
.enter().append("text")
.attr("class", function(d) { return "subunit-label " + d.NAME; })
.attr("transform", function(d) { return "translate(" + path.centroid(d) + ")"; })
.attr("fill", function(d){
var value = data.get(d.properties.NAME);
})
.attr("fill-opacity", "1")
.attr("font-size", "10px")
.attr("font-weight", "300")
.attr("text-anchor", "middle")
.text(function(d) {
return d.properties.NAME;
})
return svg.node();
}
legend = () => {
const k = 24;
const arrow = DOM.uid();
return svg`<g font-family=sans-serif font-size=10>
<g transform="translate(-${k * n / 2},-${k * n / 2}) rotate(-45 ${k * n / 2},${k * n / 2})">
<marker id="${arrow.id}" markerHeight=10 markerWidth=10 refX=6 refY=3 orient=auto>
<path d="M0,0L9,3L0,6Z" />
</marker>
${d3.cross(d3.range(n), d3.range(n)).map(([i, j]) => svg`<rect width=${k} height=${k} x=${i * k} y=${(n - 1 - j) * k} fill=${colors[j * n + i]}>
<title>${data.title[0]}${labels[j] && ` (${labels[j]})`}
${data.title[1]}${labels[i] && ` (${labels[i]})`}</title>
</rect>`)}
<line marker-end="${arrow}" x1=0 x2=${n * k} y1=${n * k} y2=${n * k} stroke=black stroke-width=1.5 />
<line marker-end="${arrow}" y2=0 y1=${n * k} stroke=black stroke-width=1.5 />
<text font-weight="bold" dy="0.71em" transform="rotate(90) translate(${n / 2 * k},6)" text-anchor="middle">${data.title[0]}</text>
<text font-weight="bold" dy="0.71em" transform="translate(${n / 2 * k},${n * k + 6})" text-anchor="middle">${data.title[1]}</text>
</g>
</g>`;
}
// Reads in CSV data and creates variables Case Rate and Death Percentage
data = Object.assign(new Map(d3.csvParse(await FileAttachment("IA_COVID19_Cases.csv").text(), ({FIPS, Deaths, Confirmed, pop_est_2018}) => [FIPS, [+Confirmed/+pop_est_2018, (+Deaths/+pop_est_2018)*100]])), {title: ["Case Rate", " % Death Percentage"]})
// http://www.joshuastevens.net/cartography/make-a-bivariate-choropleth-map/
//Creaets color schemes
// Colors can be found of the colorbrewer2.org and be ported here to create new color schemes
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"
]
}
]
labels = ["low", "", "high"]
n = Math.floor(Math.sqrt(colors.length))
x = d3.scaleQuantile(Array.from(data.values(), d => d[0]), d3.range(n))
y = d3.scaleQuantile(Array.from(data.values(), d => d[1]), d3.range(n))
//Rotate the map sets the longitude of origin for our UTM projection.
projection = d3.geoTransverseMercator().rotate([95,0]).fitExtent([[10, 10], [width, height]], ctracts);
// sets topojson to correct part of the feaeture collection
ctracts = topojson.feature(tracts, tracts.objects.ia_covid19_county)
path = d3.geoPath().projection(projection)
color = {
return value => {
if (!value) return "#ccc";
let [a, b] = value;
return colors[y(b) + x(a) * n];
};
}
//Deals wuith Null values
format = (value) => {
if (!value) return "N/A";
let [a, b] = value;
return `${a}% ${data.title[0]}${labels[x(a)] && ` (${labels[x(a)]})`}
${b}% ${data.title[1]}${labels[y(b)] && ` (${labels[y(b)]})`}`;
}
tracts = FileAttachment("ia_covid19_county.json").json()
height = 550
width = 750
topojson = require("topojson-client@3")
d3 = require("d3@5")
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.
