31:T4dd,map = { const context = DOM.context2d(width, height); const path = d3.geoPath(projection, context); context.canvas.style.maxWidth = "100%"; context.lineJoin = "round"; context.lineCap = "round"; const sofar = 0; stats.area = [0, 0] context.fillStyle="#e83F" for (let feature of topojson.feature(us, us.objects.counties).features) { stats.area[0] += feature.properties.area if (feature.properties.cum_share > share) { continue } context.beginPath(); path(feature) context.fill() if (feature.properties.cum_share > share * share) { context.fillStyle="#e836" } stats.area[1] += feature.properties.area } context.beginPath(); path(topojson.mesh(us, us.objects.counties, (a, b) => a !== b && (a.id / 1000 | 0) === (b.id / 1000 | 0))); context.lineWidth = 0.5; context.strokeStyle = "#aaa"; context.stroke(); context.beginPath(); path(topojson.mesh(us, us.objects.states, (a, b) => a !== b)); context.lineWidth = 0.5; context.strokeStyle = "#000"; context.stroke(); context.beginPath(); path(topojson.feature(us, us.objects.nation)); context.lineWidth = 1; context.strokeStyle = "#000"; context.stroke(); return context.canvas; }32:T550,us = { let area, pops; area = new Map(usCountyArea.map(d => [d.GEOID, d.ALAND])) if (year == 2020) { pops = countiesPopulation } else { // area = new Map(d3.zip([...schroeder.values("fips")], [...schroeder.values("land_sqmi")])) const s = schroeder.derive({pop: `datum => datum['dens${year}'] * datum.land_sqmi`}) pops = new Map(d3.zip([...s.values("fips")], [...s.values("pop")])) } const us = JSON.parse(JSON.stringify(raw)) for (let geo of us.objects.counties.geometries) { geo.properties.area = area.get(geo.id) geo.properties.pop = pops.get(geo.id) || 0 geo.properties.density = geo.properties.pop/geo.properties.area // yield geo.ID } const showing = new Set(states_to_show.map(d => state_info.get(d).fips)) us.objects.counties.geometries = us.objects.counties.geometries.filter(d=>d.properties.density > 0) us.objects.counties.geometries.sort((a, b) => b.properties.density - a.properties.density) us.objects.counties.geometries = us.objects.counties.geometries.filter(d => showing.has(d.id.slice(0, 2))) const total = d3.sum(us.objects.counties.geometries, d => d.properties.pop) let running = 0 for (let county of us.objects.counties.geometries) { running += county.properties.pop county.properties.cum = running county.properties.cum_share = running/total } return us }33:[{"id":"6b1776f5a0a0e76e6428805c0074a8f262e3f34b1b50944da27903e014b409958dc29b03a1c9cc331949d6a2a404c19dfd0d9d36d9c32274e6ffbc07c11350ee","href":"https://static.observableusercontent.com/files/6b1776f5a0a0e76e6428805c0074a8f262e3f34b1b50944da27903e014b409958dc29b03a1c9cc331949d6a2a404c19dfd0d9d36d9c32274e6ffbc07c11350ee","name":"counties-albers-10m.json","type":"application/octet-stream","lastModified":1644171150770.687,"size":795407}] 2f:{"title":"Getting to 75%.","cells":[{"id":0,"value":"md`# Getting to ${x}.\n\nWhat counties get you to different shares of the US population? All shaded counties get you to ${d3.format(\".0%\")(share)}, and the dark ones get you to ${d3.format(\".1%\")(share * share)}. To see an individual state, change the dropdown.\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":187,"value":"viewof share = Inputs.range([0, 1], {step: .01, label: \"Percent of populaton\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":243,"value":"viewof states_to_show = Inputs.select([...state_order], {label: \"States to show\", multiple: true, value: state_order})","pinned":false,"hidden":false,"mode":"ojs"},{"id":377,"value":"viewof year = Inputs.range([1790, 2020], {step:10, label: \"Year\", value: 2020})","pinned":false,"hidden":false,"mode":"ojs"},{"id":29,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":453,"value":"warnings = {\n let warning = ''\n if (year < 2020) {\n warning += `

Warnings

Puerto Rico, Guam, and other territories not included before 2020`\n }\n if (year < 2000) {\n warning += `
Before 2010, these are not exact statistics but instead estimates by geographer Jonathan Schroeder based on contemporary county boundaries.`\n }\n if (year < 1920) {\n warning += `
Many Native American inhabitants were not counted by the census because of the exclusion against \"Indians not Taxed\"
Showing only census statistics for the territorial United States.

${warning}

`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":476,"value":"html`

${year}

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":491,"value":"{\n map\n return html`In ${year}, ${d3.format(\".0%\")(share)} of the population is in counties comprising ${d3.format(\".1%\")(stats.area[1]/stats.area[0])} of the area`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":481,"value":"stats = ({})","pinned":true,"hidden":false,"mode":"ojs"},{"id":121,"value":"import { countiesPopulation, usCountyArea } from '@clhenrick/us-county-population-density'","pinned":true,"hidden":false,"mode":"ojs"},{"id":148,"value":"countiesPopulation","pinned":true,"hidden":false,"mode":"ojs"},{"id":233,"value":"import { state_info } from \"@bmschmidt/state-info\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":235,"value":"statenames = [...new Set([...state_info.values()].map(d => d.name))]","pinned":true,"hidden":false,"mode":"ojs"},{"id":37,"value":"import { projection, us as raw } from '@almccon/u-s-map-with-puerto-rico-us-virgin-islands-american-samoa-gua'","pinned":false,"hidden":false,"mode":"ojs"},{"id":100,"value":"width = 975","pinned":true,"hidden":false,"mode":"ojs"},{"id":101,"value":"height = 610","pinned":true,"hidden":false,"mode":"ojs"},{"id":128,"value":"us.objects.counties.geometries","pinned":true,"hidden":false,"mode":"ojs"},{"id":151,"value":"us.objects.counties.geometries[0].properties","pinned":true,"hidden":false,"mode":"ojs"},{"id":290,"value":"us.objects.counties.geometries[320].properties","pinned":true,"hidden":false,"mode":"ojs"},{"id":332,"value":"import { linear_us_state_order } from '@bmschmidt/useful-linear-orders-for-countries-and-states'","pinned":true,"hidden":false,"mode":"ojs"},{"id":413,"value":"schroeder.view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":524,"value":"schroeder.filter(d=>d.COUNTY==\"Chaffee\").view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":13,"value":"$32","pinned":true,"hidden":false,"mode":"ojs"},{"id":383,"value":"d3.zip","pinned":true,"hidden":false,"mode":"ojs"},{"id":358,"value":"schroeder = aq.fromCSV(await fetch(\"https://creatingdata.us/data/schroeder_densities.csv\").then(d => d.text())).derive({\"fips\": d => op.padstart(d.GEOID10, 5, \"0\")})","pinned":true,"hidden":false,"mode":"ojs"},{"id":371,"value":"schroeder.orderby(aq.desc('dens1850')).view()","pinned":true,"hidden":false,"mode":"ojs"},{"id":365,"value":"import {aq, op} from '@uwdata/arquero'","pinned":true,"hidden":false,"mode":"ojs"},{"id":341,"value":"state_order = [...new Set(linear_us_state_order.map(state=>state_info.get(state)).filter(d => d).map(d => d.name))]","pinned":true,"hidden":false,"mode":"ojs"},{"id":280,"value":"us.objects.counties.geometries[0].properties","pinned":true,"hidden":false,"mode":"ojs"},{"id":222,"value":"x = d3.format(\".0%\")(share)","pinned":true,"hidden":false,"mode":"ojs"},{"id":10,"value":"topojson = require(\"topojson-client@3\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":7,"value":"d3 = require(\"d3-geo@2\", 'd3-selection', 'd3-array', 'd3-format', 'd3-fetch')","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}