32:T1917,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 psychHospitals = svg .append("g") .attr("transform", "translate(20, 0)") .attr("class", "psych-hospital") .selectAll(".psych-hospital") .data(statePscyhHospitals); psychHospitals .enter() .append("circle") .attr("cx", d => projection([d[1], d[2]])[0]) .attr("cy", d => projection([d[1], d[2]])[1]) .attr("r", 4) .attr("fill", "#4b4b4b") .attr("stroke", "#fff"); psychHospitals .enter() .append("line") .attr("x1", d => projection([d[1], d[2]])[0]) .attr("y1", d => projection([d[1], d[2]])[1]) .attr("stroke", "#4b4b4b") .attr("x2", d => projection([d[1], d[2]])[0] + d[3]) .attr("y2", d => projection([d[1], d[2]])[1] + d[4]); psychHospitals .enter() .append("text") .attr("x", d => projection([d[1], d[2]])[0] + d[3]) .attr("y", d => projection([d[1], d[2]])[1] + d[4]) .attr("dx", d => d[5]) .attr("dy", d => d[6]) .text(d => d[0]) .attr("fill", "#4b4b4b") .attr("text-anchor", "middle"); 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( `Psychiatrist 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 of each year 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. Physicians with a primary area of practice of Psychiatry include the following: Child & Adolescent Psychiatry, Pediatrics - Psychiatry, Addiction Medicine, Addiction Psychiatry, Forensic Psychiatry, Geriatric Psychiatry, Hypnosis, Internal Medicine - Psychiatry, Psychiatry, Psychiatry - Family Practice, Psychoanalysis, Psychosomatic Medicine. 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: 144, 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(); }33:Te2d,psychiatry_fte = d3.csvParse(`lcntycd,fte,lcntyname,population,rate_per_10k 001,11.475,Alamance,161076,.71239668 003,2.8499999,Alexander,38452,.74118382 005,1,Alleghany,11233,.89023411 007,.1,Anson,25626,.039022867 009,.40000001,Ashe,27218,.14696157 011,4.9250002,Avery,18072,2.7252104 013,7.0999999,Beaufort,47547,1.4932593 015,0,Bertie,19881,0 017,0,Bladen,34393,0 019,7.5749998,Brunswick,131726,.57505733 021,60.325001,Buncombe,261532,2.306601 023,29.5,Burke,90246,3.2688429 025,18.625,Cabarrus,205473,.90644515 027,1.375,Caldwell,83303,.16506009 029,0,Camden,10359,0 031,.2,Carteret,70190,.028494088 033,1.7,Caswell,23699,.71732986 035,20.200001,Catawba,156949,1.2870424 037,3.3,Chatham,74835,.44097012 039,1.85,Cherokee,29216,.63321471 041,1.425,Chowan,14292,.99706125 043,.25,Clay,11488,.21761839 045,6.8499999,Cleveland,98580,.69486707 047,1.55,Columbus,56941,.27221158 049,7.1500001,Craven,103735,.68925631 051,19.775,Cumberland,329604,.59996235 053,1,Currituck,26604,.37588331 055,.30000001,Dare,36792,.081539467 057,5.4000001,Davidson,167105,.32315013 059,1.775,Davie,42727,.41542819 061,3.625,Duplin,59513,.60911059 063,104.925,Durham,306184,3.426861 065,1.1,Edgecombe,52856,.20811261 067,87.224998,Forsyth,372651,2.3406618 069,.30000001,Franklin,66514,.045103289 071,12.125,Gaston,218527,.55485135 073,1.25,Gates,11960,1.0451505 075,0,Graham,8837,0 077,57.075001,Granville,59975,9.5164652 079,1.625,Greene,21522,.75504136 081,40.625,Guilford,523962,.77534246 083,2.575,Halifax,51815,.49696034 085,2.4000001,Harnett,130847,.18342035 087,7.4749999,Haywood,62277,1.2002826 089,11.875,Henderson,116173,1.0221825 091,6.7249999,Hertford,23947,2.808285 093,0,Hoke,53343,0 095,0,Hyde,5644,0 097,12.95,Iredell,176563,.73344922 099,2.45,Jackson,43116,.56823456 101,5.3249998,Johnston,194705,.27349067 103,1,Jones,10356,.9656238 105,3.8,Lee,59337,.64040983 107,4.4250002,Lenoir,57477,.7698732 109,0,Lincoln,83251,0 111,1.2,McDowell,45716,.26249015 113,1,Macon,35413,.28238219 115,.57499999,Madison,22240,.25854316 117,.55000001,Martin,23510,.23394302 119,140.075,Mecklenburg,1077301,1.3002402 121,0,Mitchell,15237,0 123,.30000001,Montgomery,27865,.10766195 125,16.825001,Moore,97597,1.7239261 127,3.925,Nash,94365,.41593811 129,40.775002,New Hanover,227261,1.7941927 131,.1,Northampton,20709,.048288185 133,11.725,Onslow,195621,.59937328 135,120.925,Orange,142365,8.4940119 137,0,Pamlico,13268,0 139,.050000001,Pasquotank,40598,.012315878 141,.69999999,Pender,60999,.11475598 143,.75,Perquimans,13546,.55366898 145,1.65,Person,39868,.41386575 147,27.775,Pitt,176424,1.5743322 149,4.1500001,Polk,21154,1.9618039 151,2.55,Randolph,144672,.17626078 153,.44999999,Richmond,44892,.10024057 155,6.0749998,Robeson,132020,.46015754 157,4,Rockingham,91790,.43577731 159,9.1999998,Rowan,141917,.64826626 161,3.8,Rutherford,67796,.56050503 163,1.75,Sampson,63143,.27714869 165,.875,Scotland,35686,.2451942 167,4.8249998,Stanly,62443,.77270466 169,1.775,Stokes,46728,.3798579 171,3.6500001,Surry,72843,.50107765 173,1.25,Swain,14999,.83338886 175,2.45,Transylvania,34464,.71088672 177,.2,Tyrrell,4138,.48332527 179,5.75,Union,228171,.25200397 181,2.7,Vance,44862,.60184568 183,178.375,Wake,1048771,1.7008003 185,1.325,Warren,20133,.65812349 187,.40000001,Washington,12349,.32391286 189,2.425,Watauga,56170,.43172511 191,30.525,Wayne,124945,2.4430749 193,4.1500001,Wilkes,70536,.58835208 195,5.4499998,Wilson,82035,.66435057 197,2.125,Yadkin,37687,.56385493 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 } })34:T501,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 = `≥ ${currentRange[0]}`) : (currentRangeText = currentRangeText); return { color: d, range: currentRangeText }; }); colorRange.reverse(); colorRange.push({ color: "#fff", range: "No Psychiatrists" }); let fontColor = "#4b4b4b"; return svg`Psychiatry FTEs per 10,000 Population(# of counties)${colorRange.map( (d, i) => `${ d.range } (${bins.get(d.color)})` )}`; }35:[] 30:{"title":"Psychiatrist Full-Time Equivalents per 10,000 Population North Carolina, 2017","cells":[{"id":0,"value":"md`## Psychiatrist Full-Time Equivalents per 10,000 Population North Carolina, 2017\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"$32","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":221,"value":"DOM.download(serialize(map), \"psych_fte.svg\", \"Download Map as SVG\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":248,"value":"DOM.download(await rasterize(map), \"psych_fte.png\",\"Download Map as PNG\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":525,"value":"statePscyhHospitals = [\n [\"Broughton Hospital\", -81.676612, 35.722589, -60, -80, -35, -5],\n [\"Cherry Hospital\", -78.020303, 35.394605, 80, 150, 20, 15],\n [\"Central Regional Hospital\", -78.771185, 36.145426, -20, -70, 0, -5]\n] //name, long, lat, x line offset, y line offset, text dx, text dy","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(psychiatry_fte.map(d=> [d.fips, d.rate_per_10k]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":328,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":390,"value":"nc_rate_per_10k = d3.sum(psychiatry_fte, d=>d.fte)/d3.sum(psychiatry_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 = psychiatry_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":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"md`North Carolina county boundary file.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"nc = d3.json(\n \"https://gist.githubusercontent.com/gallowayevan/1b6056fdccb0aa0d860cbdee2bdf7597/raw/a7a6f4d80d077e74152e6c3196abdec9b899eb76/ncmap.json\"\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":69,"value":"import {slider, checkbox} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":86,"value":"schemes = [\"Blues\",\n \"Greens\",\n \"Greys\",\n \"Oranges\",\n \"Purples\",\n \"Reds\",\n \"BuGn\",\n \"BuPu\",\n \"GnBu\",\n \"OrRd\",\n \"PuBuGn\",\n \"PuBu\",\n \"PuRd\",\n \"RdPu\",\n \"YlGnBu\",\n \"YlGn\",\n \"YlOrBr\",\n \"YlOrRd\"\n ]","pinned":false,"hidden":false,"mode":"ojs"},{"id":91,"value":"cluster = require(\"https://unpkg.com/d3-scale-cluster@1.1.7/dist/d3-scale-cluster.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":205,"value":"import {logo} from \"@gallowayevan/sheps-health-workforce-nc-logo\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":224,"value":"import {serialize, rasterize} from \"@mbostock/saving-svg\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":259,"value":"import {createSVGtext} from \"@gallowayevan/svg-word-wrap\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":409,"value":"import {omb_metro_2017} from '@gallowayevan/change-in-health-professional-supply-over-time-north-carol'","pinned":false,"hidden":false,"mode":"ojs"},{"id":512,"value":"import {groupCount} from \"@mbostock/group\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":2,"value":"d3 = require(\"d3\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W35","stdlib":"1","titling":"auto"}