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2a:null 2b:["$","title",null,{"children":"Assignment 4: Bivariate Choropleth Mapping | Angelina Evans | Observable"}] 31:T6f7,md`# Urban and Rural Population of New York This is a bivariate choropleth map of the 62 counties in New York. The data is from the census 20 years ago. The two variables I created are the percentage of rural population and the percentage of urban population. To see the names of the county and the percentages of the variables, put the mouse over the county. The class scheme is quantile, which means the classes are split into equal range values. I found that most of the counties belong in the extreme groups: Counties with high urban, low rural and counties with high rural, low urban. Counties with high urban, low rural: Niagara, Erie, Monroe, Chemung, Onondaga, Schenectady, Albany, Rensselaer, Kings, Queens, New York, Suffolk, Bronx, Westchester, Rockland, Richmond, and Nassau. I noticed that the counties at the southernmost part of the state (Kings, Queens, New York, Suffolk, Bronx, Westchester, Rockland, Richmond, and Nassau) contain hardly any rural population at all. In fact, the percent rural population of the counties Bronx, Kings, Queens, Richmond, and New York is exactly 0 percent. The other counties mentioned in the parentheses above range from 2 percent to almost zero. The most populated county is Kings County (Brooklyn) and had a population of 2,465,326 in 2000. Counties with high rural, low urban: Allegany, Yutes, Schuyler, Chenango, Oswego, Lewis, St. Lawrence, Otsego, Delaware, Sullivan, Greene, Columbia, Schoharie, Washington, Hamilton, Essex, and Franklin. Hamilton County the only county with 0 percent urban population. It is the county with the smallest population of New York (5,379 in 2000). There is lots of variety when it comes to these variables. It is interesting to observe the patterns the bivariate map gives. `32:T44c,legend = () => { const k = 24; const arrow = DOM.uid(); return svg` ${d3.cross(d3.range(n), d3.range(n)).map(([i, j]) => svg` ${data.title[0]}${labels[j] && ` (${labels[j]})`} ${data.title[1]}${labels[i] && ` (${labels[i]})`} `)} ${data.title[0]} ${data.title[1]} `; }33:[{"id":"114d7cf2491be1560fa5760e857559b605c2f87f3bc2d2479b400471a6d5413eca1caaabafcad618225560e56b55ce7cfad3e68e70a0d5240ac1734a42f79415","href":"https://static.observableusercontent.com/files/114d7cf2491be1560fa5760e857559b605c2f87f3bc2d2479b400471a6d5413eca1caaabafcad618225560e56b55ce7cfad3e68e70a0d5240ac1734a42f79415","name":"NewYork_Table.csv","type":"text/csv","lastModified":1586361451901.041,"size":27346},{"id":"b2af8053fae1902344e833eb564c5202ea68a218ac3004b7caa1bcce4421b2e3d0dd205738d81579a6e2bf2bccda88e0007fde2895cb32f3cd62bcf91fc8d309","href":"https://static.observableusercontent.com/files/b2af8053fae1902344e833eb564c5202ea68a218ac3004b7caa1bcce4421b2e3d0dd205738d81579a6e2bf2bccda88e0007fde2895cb32f3cd62bcf91fc8d309","name":"NewYork.json","type":"application/json","lastModified":1586361493318.034,"size":164357}] 2e:{"id":"6f8f04eec71f47c2","slug":"assignment-4-bivariate-choropleth-mapping","title":"Assignment 4: Bivariate Choropleth Mapping","thumbnail":"cb49a2880970bf4aba5bf1108b9dac3e7b33de01ae16824d3a4e6cd69b7852ee","access_level":"public","create_time":"$D2020-04-06T15:28:01.527Z","update_time":"$D2020-05-04T23:21:09.243Z","view_time":null,"first_public_time":"$D2020-04-11T21:43:39.348Z","fork":{"id":"de68dfd4266dab75","slug":"bivariate-choropleth-mapping","title":"Bivariate Choropleth Mapping","owner":{"id":"1522f7962f5f1185","login":"caglarkoylu","name":"Caglar Koylu"}},"stars":0,"starred":false,"owner":{"type":"team","id":"2410ef09c7df7ffa","login":"1angelinaevans","name":"Angelina Evans ","avatar_url":"https://avatars-next.observableusercontent.com/4f3dac6701f8b9c89f58726b00177f4d8588e10da654a66493613635a726e9b7","tier":"starter_2024"},"version":593,"publish_version":593,"role":null,"authored":false,"authors":[{"type":"individual","id":"c446089dc10aca9b","login":"1angelinaevans","name":"Angelina Evans ","avatar_url":"https://avatars-next.observableusercontent.com/4f3dac6701f8b9c89f58726b00177f4d8588e10da654a66493613635a726e9b7","tier":null}],"members":[{"type":"individual","id":"c446089dc10aca9b","login":"1angelinaevans","name":"Angelina Evans ","avatar_url":"https://avatars-next.observableusercontent.com/4f3dac6701f8b9c89f58726b00177f4d8588e10da654a66493613635a726e9b7","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Assignment 4: Bivariate Choropleth Mapping","cells":[{"id":0,"value":"md`# Assignment 4: Bivariate Choropleth Mapping\n\nUrban and Rural Population of New York.\nData from the 2000 Census.\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":194,"value":"viewof colors = {\n const form = html`

color scheme`;\n form.i.selectedIndex = 1;\n form.oninput = () => form.value = schemes[form.i.selectedIndex].colors;\n form.oninput();\n return form;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":14,"value":"chart = {\n const svg = d3.create(\"svg\")\n .attr(\"viewBox\", [0, 0, width, height]);\n\n svg.append(legend)\n .attr(\"transform\", \"translate(190,150)\");\n\n svg.append(\"g\")\n .selectAll(\"path\")\n .data(topojson.feature(polygons, polygons.objects. cty036).features)\n .join(\"path\")\n .attr(\"stroke\", \"white\")\n .attr(\"fill\", d => color(data.get(d.properties[idAttribute])))\n .attr(\"d\", path)\n .append(\"title\")\n .text(d => `${d.properties[idAttribute]}, ${format(data.get(d.properties[idAttribute]))}`);\n\n return svg.node();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":561,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":359,"value":"// http://www.joshuastevens.net/cartography/make-a-bivariate-choropleth-map/\nschemes = [\n {\n name: \"RdBu\", \n colors: [\n \"#e8e8e8\", \"#e4acac\", \"#c85a5a\",\n \"#b0d5df\", \"#ad9ea5\", \"#985356\",\n \"#64acbe\", \"#627f8c\", \"#574249\"\n ]\n },\n {\n name: \"BuPu\", \n colors: [\n \"#e8e8e8\", \"#ace4e4\", \"#5ac8c8\",\n \"#dfb0d6\", \"#a5add3\", \"#5698b9\", \n \"#be64ac\", \"#8c62aa\", \"#3b4994\"\n ]\n },\n {\n name: \"GnBu\", \n colors: [\n \"#e8e8e8\", \"#b5c0da\", \"#6c83b5\",\n \"#b8d6be\", \"#90b2b3\", \"#567994\",\n \"#73ae80\", \"#5a9178\", \"#2a5a5b\"\n ]\n },\n {\n name: \"PuOr\", \n colors: [\n \"#e8e8e8\", \"#e4d9ac\", \"#c8b35a\",\n \"#cbb8d7\", \"#c8ada0\", \"#af8e53\",\n \"#9972af\", \"#976b82\", \"#804d36\"\n ]\n }\n]","pinned":true,"hidden":false,"mode":"ojs"},{"id":216,"value":"labels = [\"low\", \"med\", \"high\"]","pinned":true,"hidden":false,"mode":"ojs"},{"id":207,"value":"n = Math.floor(Math.sqrt(colors.length))","pinned":true,"hidden":false,"mode":"ojs"},{"id":209,"value":"x = d3.scaleQuantile(Array.from(data.values(), d => d[0]), d3.range(n))","pinned":true,"hidden":false,"mode":"ojs"},{"id":204,"value":"y = d3.scaleQuantile(Array.from(data.values(), d => d[1]), d3.range(n))","pinned":true,"hidden":false,"mode":"ojs"},{"id":486,"value":"path = d3.geoPath().projection(projection)","pinned":true,"hidden":false,"mode":"ojs"},{"id":462,"value":"//Rotate the map sets the longitude of origin for our UTM projection.\nprojection = d3.geoTransverseMercator().rotate([79,0]).fitExtent([[10, 10], [width, height]], polygon_features);","pinned":true,"hidden":false,"mode":"ojs"},{"id":430,"value":"polygon_features = topojson.feature(polygons, polygons.objects. cty036)","pinned":true,"hidden":false,"mode":"ojs"},{"id":467,"value":"data = Object.assign(new Map(d3.csvParse(await FileAttachment(\"NewYork_Table.csv\").text(), ({NAME, URBAN, RURAL, POP2000}) => [NAME, [(+URBAN/+POP2000)*100,(+RURAL/+POP2000)*100]])), {title: [\"Percent Urban\", \"Percent Rural\"]})","pinned":true,"hidden":false,"mode":"ojs"},{"id":483,"value":"idAttribute = \"NAME\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":8,"value":"polygons = FileAttachment(\"NewYork.json\").json()","pinned":true,"hidden":false,"mode":"ojs"},{"id":427,"value":"height = 810","pinned":true,"hidden":false,"mode":"ojs"},{"id":424,"value":"width = 875","pinned":true,"hidden":false,"mode":"ojs"},{"id":480,"value":"$32","pinned":true,"hidden":false,"mode":"ojs"},{"id":477,"value":"color = {\n return value => {\n if (!value) return \"#ccc\";\n let [a, b] = value;\n return colors[y(b) + x(a) * n];\n };\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":474,"value":"format = (value) => {\n if (!value) return \"N/A\";\n let [a, b] = value;\n return `${a} ${data.title[0]}${labels[x(a)] && ` (${labels[x(a)]})`}\n${b}% ${data.title[1]}${labels[y(b)] && ` (${labels[y(b)]})`}`;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":6,"value":"topojson = require(\"topojson-client@3\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":3,"value":"d3 = require(\"d3@5\")","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}} 2f:"$2e:body"