30:T140b,map = { const width = 960; const height = 600; const rateFormat = d3.format(".2r"); let fills = []; const projection = d3 .geoAlbers() .rotate([0, 62, 0]) .fitSize([width - 40, height - 40], nc); const path = d3.geoPath(projection); const countyCentroids = nc.features .filter( d => omb_metro_2017.get(d.properties.county.toUpperCase()) == "nonmetro" ) .map(d => path.centroid(d)); const svg = d3 .select(DOM.svg(width, height)) .style("width", "100%") .style("height", "auto"); svg .append("rect") .attr("width", "100%") .attr("height", "100%") .attr("fill", "#fff"); svg .append("g") .selectAll("path") .data(nc.features) .enter() .append("path") .attr("d", path) .attr("transform", "translate(20, 0)") .attr("class", "counties") .attr("stroke", "#333") .style("stroke-width", 2) .style("fill", d => { const fill = getFill(d.properties.FIPS_integ); fills.push(fill); return fill; }) .on("mouseover", d => d3 .selectAll(".mapCaption") .text( `${d.properties.county} County: ${rateFormat( dataMap.get(d.properties.FIPS_integ.toString()) )} FTEs per 10,000 population` ) ) .on("mouseout", d => d3 .selectAll(".mapCaption") .text( `North Carolina: ${rateFormat( nc_rate_per_10k )} FTEs per 10,000 population` ) ); const titleText = svg .append("text") .attr("transform", "translate(20, 40)") .style("fill", "#4b4b4b"); titleText .append("tspan") .attr("class", "mapTitle") .attr("font-size", "1.4rem") .text( `Maternal & Fetal Medicine Full-Time Equivalents per 10,000 Population, North Carolina, 2017` ); titleText .append("tspan") .attr("class", "mapCaption") .attr("font-size", "1rem") .text( `North Carolina: ${rateFormat( nc_rate_per_10k )} FTEs per 10,000 population` ) .attr("dy", "1.4em") .attr("x", 0); svg.node().appendChild( createSVGtext({ text: "Notes: Data include active, licensed physicians in practice in North Carolina as of October 31, 2017 who reported a primary area of practice of Maternal & Fetal Medicine who are not residents-in-training and are not employed by the Federal government. Physician data are derived from the North Carolina Medical Board. Population census data and estimates are downloaded from the North Carolina Office of State Budget and Management via NC LINC and are based on US Census data. Source: North Carolina Health Professions Data System, Program on Health Workforce Research and Policy, Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill. ", x: width * 0.05, y: height * 0.86, fill: "#4b4b4b", maxCharsPerLine: 140, fontSize: 10 }) ); // let urbanized = svg.append("g") // .selectAll("path") // .data(nc_urbanized_areas.features) // .enter() // .append("path") // .attr("d", path) // .attr("transform", "translate(20, 0)") // .attr("class", "urbanized-areas") // .attr("stroke", "#fff")//"#4b4b4b") // .style("stroke-width", 1) // .style("fill", "none") // .style("pointer-events", "none"); const legend = svg .append("g") .attr("class", "legend") .attr("transform", "translate(50,350)"); const bins = groupCount(fills, d => d); legend.node().appendChild(createLegendCells(colorScale, bins)); // svg.node().appendChild(urbanizedExample); // svg.append("text").attr("transform", "translate(280, 465)").style("fill", "#4b4b4b").text("Census Urbanized Areas"); // d3.select(svg.node().appendChild(urbanized.node().parentNode.cloneNode(true))) // .attr("transform","translate(20,20)"); // d3.select(svg.node().appendChild(logo.childNodes[0].cloneNode(true))) // d3.select(svg.node().appendChild(logo.childNodes[2].cloneNode(true))) // .attr("transform",`translate(${width*.65},${height*.9}) scale(0.5)`); const symbolGenerator = d3 .symbol() .type(d3.symbolStar) .size(60); svg .selectAll(".stars") .data(countyCentroids) .enter() .append("path") .attr("class", "stars") .attr("transform", d => `translate(${d[0] + 20},${d[1]})`) .attr("d", symbolGenerator) .attr("fill", "#fff") .attr("stroke", "#333"); const ruralLegend = svg.append("g").attr("transform", "translate(280, 465)"); ruralLegend .append("path") .attr("d", symbolGenerator) .attr("fill", "#fff") .attr("stroke", "#333"); ruralLegend .append("text") .attr("dx", 15) .attr("dy", 5) .attr("fill", "#333") .text("Nonmetropolitan County (54)"); d3.select(svg.node().appendChild(logo.childNodes[0].cloneNode(true))); d3.select(svg.node().appendChild(logo.childNodes[2].cloneNode(true))).attr( "transform", `translate(750,502) scale(0.35)` ); svg.selectAll("text").attr("font-family", "sans-serif"); return svg.node(); }31:Ta85,profession_fte = d3.csvParse(`lcntycd,fte,lcntyname,population,rate_per_10k 001,.27083334,Alamance,161076,.01681401 017,.10416666,Bladen,34393,.030287171 021,1.7916666,Buncombe,261532,.068506591 025,1.25,Cabarrus,205473,.060835242 035,.625,Catawba,156949,.039821852 051,.9375,Cumberland,329604,.028443223 063,10.895833,Durham,306184,.35585898 067,11.5,Forsyth,372651,.30859974 071,.9375,Gaston,218527,.042900879 081,1.3125,Guilford,523962,.025049526 091,.875,Hertford,23947,.36539024 119,9.3125,Mecklenburg,1077301,.08644288 125,.83333331,Moore,97597,.085385136 129,3.5416667,New Hanover,227261,.15584138 135,10.520833,Orange,142365,.73900419 147,3.25,Pitt,176424,.18421529 183,7.8125,Wake,1048771,.074491955 003,0,Alexander,38452,0 005,0,Alleghany,11233,0 007,0,Anson,25626,0 009,0,Ashe,27218,0 011,0,Avery,18072,0 013,0,Beaufort,47547,0 015,0,Bertie,19881,0 019,0,Brunswick,131726,0 023,0,Burke,90246,0 027,0,Caldwell,83303,0 029,0,Camden,10359,0 031,0,Carteret,70190,0 033,0,Caswell,23699,0 037,0,Chatham,74835,0 039,0,Cherokee,29216,0 041,0,Chowan,14292,0 043,0,Clay,11488,0 045,0,Cleveland,98580,0 047,0,Columbus,56941,0 049,0,Craven,103735,0 053,0,Currituck,26604,0 055,0,Dare,36792,0 057,0,Davidson,167105,0 059,0,Davie,42727,0 061,0,Duplin,59513,0 065,0,Edgecombe,52856,0 069,0,Franklin,66514,0 073,0,Gates,11960,0 075,0,Graham,8837,0 077,0,Granville,59975,0 079,0,Greene,21522,0 083,0,Halifax,51815,0 085,0,Harnett,130847,0 087,0,Haywood,62277,0 089,0,Henderson,116173,0 093,0,Hoke,53343,0 095,0,Hyde,5644,0 097,0,Iredell,176563,0 099,0,Jackson,43116,0 101,0,Johnston,194705,0 103,0,Jones,10356,0 105,0,Lee,59337,0 107,0,Lenoir,57477,0 109,0,Lincoln,83251,0 111,0,McDowell,45716,0 113,0,Macon,35413,0 115,0,Madison,22240,0 117,0,Martin,23510,0 121,0,Mitchell,15237,0 123,0,Montgomery,27865,0 127,0,Nash,94365,0 131,0,Northampton,20709,0 133,0,Onslow,195621,0 137,0,Pamlico,13268,0 139,0,Pasquotank,40598,0 141,0,Pender,60999,0 143,0,Perquimans,13546,0 145,0,Person,39868,0 149,0,Polk,21154,0 151,0,Randolph,144672,0 153,0,Richmond,44892,0 155,0,Robeson,132020,0 157,0,Rockingham,91790,0 159,0,Rowan,141917,0 161,0,Rutherford,67796,0 163,0,Sampson,63143,0 165,0,Scotland,35686,0 167,0,Stanly,62443,0 169,0,Stokes,46728,0 171,0,Surry,72843,0 173,0,Swain,14999,0 175,0,Transylvania,34464,0 177,0,Tyrrell,4138,0 179,0,Union,228171,0 181,0,Vance,44862,0 185,0,Warren,20133,0 187,0,Washington,12349,0 189,0,Watauga,56170,0 191,0,Wayne,124945,0 193,0,Wilkes,70536,0 195,0,Wilson,82035,0 197,0,Yadkin,37687,0 199,0,Yancey,18199,0 `, function(d){ return { fips : "37" + d.lcntycd, fte : +d.fte, county : d.lcntyname, population: +d.population, rate_per_10k: +d.rate_per_10k } })32:T4f1,createLegendCells = (colorScale, bins) => { let colorRange = colorScale.range().map(function(d, i, array) { let currentRange = colorScale.invertExtent(d).map(d3.format(".2f")); let currentRangeText = `${currentRange[0]} to ${currentRange[1]}`; i == 0 ? (currentRangeText = `< ${currentRange[1]}`) : i == array.length - 1 ? (currentRangeText = `≥ ${currentRange[0]}`) : (currentRangeText = currentRangeText); return { color: d, range: currentRangeText }; }); colorRange.reverse(); colorRange.push({ color: "#fff", range: "No MFMs" }); let fontColor = "#4b4b4b"; return svg`MFM FTEs per 10,000 Population(# of counties)${colorRange.map( (d, i) => `${ d.range } (${bins.get(d.color)})` )}`; }33:[] 2e:{"title":"","cells":[{"id":0,"value":"md`## Maternal & Fetal Medicine Full-Time Equivalents per 10,000 Population North Carolina, 2017\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":84,"value":"viewof colorScheme = html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":89,"value":"viewof numberOfBins = slider({\n min: 3, \n max: 5, \n step: 1, \n value: 5, \n title: \"Number of Bins\", \n description: \"Select number of bins for each color scale\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":44,"value":"md`## Appendix`","pinned":false,"hidden":false,"mode":"ojs"},{"id":40,"value":"md`Urbanized areas are from the [US Census Cartographic Boundary File](https://www.census.gov/geo/maps-data/data/cbf/cbf_ua.html), clipped to North Carolina.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":10,"value":"nc_urbanized_areas = d3.json(\n \"https://gist.githubusercontent.com/gallowayevan/60d3f0f67e80c5c5b5a4b4e199993f5b/raw/20edf0dd2092f8b2675116558ac8335697bd77c2/nc_urbanized_areas_simplified_clipped.json\"\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":37,"value":"md`Population data derived from North Carolina Office of State Budget and Management (OSBM) estimates and projections: https://www.osbm.nc.gov/demog/county-projections`","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"dataMap = new Map(profession_fte.map(d=> [d.fips, d.rate_per_10k]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":328,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":390,"value":"nc_rate_per_10k = d3.sum(profession_fte, d=>d.fte)/d3.sum(profession_fte, d=>d.population) * 10000","pinned":false,"hidden":false,"mode":"ojs"},{"id":81,"value":"colorScale = {\t\t\t \t\t\t\n const scheme = d3[\"scheme\" + colorScheme][numberOfBins];\n const scale = cluster()\n \t\t\t\t\t\t.domain(domain)\n \t\t\t\t\t\t.range(scheme);\n \n \t\t\treturn scale;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":175,"value":"domain = profession_fte.map(d => d.rate_per_10k)","pinned":false,"hidden":false,"mode":"ojs"},{"id":47,"value":"getFill = (fips) => {\n const currentValue = dataMap.get(fips.toString());\n\n \treturn currentValue == 0 ? \"#fff\" : colorScale(currentValue);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":95,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"md`North Carolina county boundary file.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"nc = d3.json(\n \"https://gist.githubusercontent.com/gallowayevan/1b6056fdccb0aa0d860cbdee2bdf7597/raw/a7a6f4d80d077e74152e6c3196abdec9b899eb76/ncmap.json\"\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":69,"value":"import {slider, checkbox} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":86,"value":"schemes = [\"Blues\",\n \"Greens\",\n \"Greys\",\n \"Oranges\",\n \"Purples\",\n \"Reds\",\n \"BuGn\",\n \"BuPu\",\n \"GnBu\",\n \"OrRd\",\n \"PuBuGn\",\n \"PuBu\",\n \"PuRd\",\n \"RdPu\",\n \"YlGnBu\",\n \"YlGn\",\n \"YlOrBr\",\n \"YlOrRd\"\n ]","pinned":false,"hidden":false,"mode":"ojs"},{"id":91,"value":"cluster = require(\"https://unpkg.com/d3-scale-cluster@1.1.7/dist/d3-scale-cluster.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":205,"value":"import {logo} from \"@gallowayevan/sheps-health-workforce-nc-logo\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":224,"value":"import {serialize, rasterize} from \"@mbostock/saving-svg\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":259,"value":"import {createSVGtext} from \"@gallowayevan/svg-word-wrap\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":409,"value":"import {omb_metro_2017} from '@gallowayevan/change-in-health-professional-supply-over-time-north-carol'","pinned":false,"hidden":false,"mode":"ojs"},{"id":512,"value":"import {groupCount} from \"@mbostock/group\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":2,"value":"d3 = require(\"d3\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}