choropleth = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
svg.append("g")
.attr("transform", "translate(650,700)")
.append(() =>
legend({
color: color,
title: data.title,
width: 300,
tickFormat: ".3f"
})
);
svg.append("g")
.selectAll("path")
.data(tracts_features.features)
.join("path")
.attr("stroke", "black")
.attr("stroke-linejoin", "round")
.attr("stroke-width", .75)
// .attr("fill", function(d){
// console.log(color(data.get(d.properties.FIPS)[0]))
// return color(data.get(d.properties.FIPS)[0]);
// })
.attr("fill", d => color(data.get(d.properties.GEOID_NUM)))
.attr("d", path)
.append("title")
.text(d => " Male Percentage: " + data.get(d.properties.GEOID_NUM));
return svg.node();
}
d3 = require("d3@5")
import {legend} from "@d3/color-legend"
simple = require("simple-statistics@7.0.7/dist/simple-statistics.min.js")
format = d => `${d}%`
topojson = require("topojson-client@3")
tracts = FileAttachment("DenverCOTracts.json").json()
tracts_features = topojson.feature(tracts, tracts.objects.DenverCOTracts)
csv_data = d3.csvParse(await FileAttachment("census_tracts_2010.csv").text(),({GEOID_NUM, POPULATION_2010, MALE, FEMALE}) => [+GEOID_NUM, +MALE/+POPULATION_2010])
data = Object.assign(new Map(csv_data), {title: ["Percent Population of Denver, CO: Male"]})
malepct = Array.from(csv_data.values(), d => d[1])
IncBlu = [d3.color("#eff3ff"), d3.color("#bdd7e7"), d3.color("#6baed6"), d3.color("#3182bd"),d3.color("#08519c")]
naturalbreaks = simple.ckmeans(malepct, IncBlu.length).map(v => v.pop())
//more information on sequential scales: https://observablehq.com/@d3/sequential-scales
// color = d3.scaleSequentialQuantile([...data.values()], d3.interpolateBlues)
// color = d3.scaleQuantile()
// .domain(med_age)
// .range()
color = d3.scaleQuantile()
.domain(malepct)
.range(IncBlu)
width = 1000
height = 800
margin = 100
//Rotate the map sets the longitude of origin for our UTM Zone 15N projection.
//projection = d3.geoTransverseMercator().rotate([94,0]).fitExtent([[80, 80], [width, height]], tracts_features);
//d3 reference for projections: https://github.com/d3/d3-geo/blob/master/README.md
//use the following url for specific projection settings: https://github.com/veltman/d3-stateplane
//Use this code to set up the map projection (if different than geographic projection)
//projection = d3.geoAlbers().fitExtent([[margin, margin], [width - margin, height - margin]], counties)
//projection = d3.geoMercator().fitExtent([[margin, margin], [width - margin, height - margin]], counties)
projection = d3.geoConicConformal()
.parallels([38 + 27 / 60, 39 + 45 / 60])
.rotate([105 + 30 / 60, 0]).fitExtent([[80, 80], [width, height]], tracts_features);
//Using a path generator to project geometry onto the map
path = d3.geoPath().projection(projection);
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.
