31:[{"id":"538901cdd8f8d058535938968b6e8e86f19e58eaba2c2bd76bbedaba20c0ee23aa836022ed3dd87b7ec9d0d5204f22ece15c9554bfc531e6806349cc1cb23c62","href":"https://static.observableusercontent.com/files/538901cdd8f8d058535938968b6e8e86f19e58eaba2c2bd76bbedaba20c0ee23aa836022ed3dd87b7ec9d0d5204f22ece15c9554bfc531e6806349cc1cb23c62","name":"Census_Tracts_in_2020.geojson","type":"application/geo+json","lastModified":1714078467504.191,"size":2691682},{"id":"e47b45f86c638ef5a1222e7b7a6c45ba4fe924180f19f2da4d4ecc44894e44059e8a0d043a8ea2843a0cebbd0cdd3c654d95bb7630521360353fce98e70f0d3f","href":"https://static.observableusercontent.com/files/e47b45f86c638ef5a1222e7b7a6c45ba4fe924180f19f2da4d4ecc44894e44059e8a0d043a8ea2843a0cebbd0cdd3c654d95bb7630521360353fce98e70f0d3f","name":"dc race and income.csv","type":"text/csv","lastModified":1714078538464.144,"size":45631},{"id":"df1e457ee996411ee94a80085adb19143744838e1d9b1a59268bd01d39c7336e74dc4d7421f90b02c1c0e24eb1a6711d4f31c09a8a905d18bbfbd59ce869909d","href":"https://static.observableusercontent.com/files/df1e457ee996411ee94a80085adb19143744838e1d9b1a59268bd01d39c7336e74dc4d7421f90b02c1c0e24eb1a6711d4f31c09a8a905d18bbfbd59ce869909d","name":"dc arrests lat lon.csv","type":"text/csv","lastModified":1714078919958.915,"size":465180}] 2f:{"title":"Washington DC Arrests - 2023","cells":[{"id":596,"value":"t1 = md`# Washington DC Arrests - 2023`","pinned":false,"hidden":false,"mode":"ojs"},{"id":101,"value":"viewof granularity = slider({\n min: 1,\n max: 25,\n step: 1,\n value: 16,\n title: \"Granularity\",\n description: \"Slide to the right to see more granular data on the heatmap\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":142,"value":"viewof selection = Inputs.radio([\"Black\", \"Latino\", \"White\", \"income\"], {\n value: \"Black\",\n label: \"Choose comparison map\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":363,"value":"container = html`\n \n \n \n

Heatmap of Washington, DC Arrests

\n
\n ${heatmap}\n

${title}

\n ${chart_selection}\n

\n \n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":817,"value":"### Plot of 2023 DC Arrests by Race","pinned":false,"hidden":false,"mode":"md"},{"id":804,"value":"dotmap = Plot.plot({\n color: {\n domain: [\"ASIAN\", \"BLACK\", \"MULTIPLE\", \"WHITE\"],\n scheme: \"set1\",\n legend: true\n },\n projection: { type: \"reflect-y\", domain: dc },\n marks: [\n Plot.dot(arrests, {\n x: \"arrest_longitude\",\n y: \"arrest_latitude\",\n bandwidth: 25 - granularity,\n fill: \"defendant_race\",\n opacity: 0.2,\n r: 1.8\n }),\n Plot.geo(dc, { strokeOpacity: 0.3 })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":588,"value":"#### Data","pinned":false,"hidden":false,"mode":"md"},{"id":42,"value":"arrests = FileAttachment(\"dc arrests lat lon.csv\").csv({ typed: true })","pinned":false,"hidden":false,"mode":"ojs"},{"id":4,"value":"// https://opdatahub.dc.gov/datasets/95f1885eff9a4c089012a872c851c50a/explore\ndc = FileAttachment(\"Census_Tracts_in_2020.geojson\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":240,"value":"flattened = dc.features.map((d) => ({\n ...d,\n id: d.properties.GEOID\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":126,"value":"race_income_data = FileAttachment(\"dc race and income.csv\")\n .csv({\n typed: false\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":263,"value":"id = race_income_data.map((d) => ({\n ...d,\n id: d.geoid10,\n number: Number(d.value)\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":139,"value":"mapped_data = new Map(\n id\n .filter((d) => selection.includes(d.variable))\n .map(({ id, number }) => [id, number])\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":540,"value":"income_data = new Map(\n id\n .filter((d) => [\"income\"].includes(d.variable) & (d.number > 5000))\n .map(({ id, number }) => [id, number])\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"d3 = require(\"d3\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":414,"value":"level_data = [\n {\n class: \"Felony\",\n Arrests: \"156426\"\n },\n\n {\n class: \"Misdemeanor\",\n Arrests: \"324635\"\n },\n {\n class: \"Local Ordinance or Petty Offense\",\n Arrests: \"72693\"\n },\n {\n class: \"Unknown\",\n Arrests: \"85776\"\n },\n {\n class: \"\"\n }\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":582,"value":"#### Dependencies and local logic","pinned":false,"hidden":false,"mode":"md"},{"id":557,"value":"title = selection == \"income\"\n ? `Washington, DC Census Tracts by Median Income \\n \\n(2022 American Community Survey)`\n : `Percent of Residents Who Are ${selection} by Census Tract (2020 Census)`","pinned":true,"hidden":false,"mode":"ojs"},{"id":561,"value":"chart_selection = selection == \"income\" ? income_map : demographic_map","pinned":true,"hidden":false,"mode":"ojs"},{"id":110,"value":"import { slider } from \"@jashkenas/inputs\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":579,"value":"#### Style","pinned":false,"hidden":false,"mode":"md"},{"id":521,"value":"html``","pinned":false,"hidden":false,"mode":"html"},{"id":523,"value":"html``","pinned":false,"hidden":false,"mode":"html"},{"id":577,"value":"#### Detached maps","pinned":false,"hidden":false,"mode":"md"},{"id":131,"value":"demographic_map = Plot.plot({\n projection: { type: \"reflect-y\", domain: dc },\n color: {\n scheme: \"blues\",\n unknown: \"#ddd\",\n type: \"linear\",\n label: `% of tract population that is ${selection}`,\n legend: true,\n percent: true,\n domain: [0, 100]\n },\n\n marks: [\n Plot.geo(flattened, {\n stroke: \"black\",\n type: \"linear\", // Linear scale for color progression\n legend: true,\n title: (d) => mapped_data.get(d.id),\n fill: (d) => mapped_data.get(d.id),\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":11,"value":"heatmap = Plot.plot({\n color: {\n scheme: \"blues\"\n },\n marginTop: 78,\n projection: { type: \"reflect-y\", domain: dc },\n marks: [\n Plot.density(arrests, {\n x: \"arrest_longitude\",\n y: \"arrest_latitude\",\n bandwidth: 25 - granularity,\n fill: \"density\"\n }),\n Plot.geo(dc, { strokeOpacity: 0.3 })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":534,"value":"income_map = Plot.plot({\n projection: { type: \"reflect-y\", domain: dc },\n color: {\n scheme: \"spectral\", // Change color scheme\n unknown: \"#ddd\", // Polygons with unknown broadband values are gray\n type: \"linear\", // Linear scale for color progression\n label: \"Median household income\",\n domain: [15000, 250000],\n legend: true\n },\n\n marks: [\n Plot.geo(flattened, {\n stroke: \"black\",\n type: \"linear\", // Linear scale for color progression\n legend: true,\n fill: (d) => income_data.get(d.id),\n tip: true\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W31","stdlib":"1","titling":"auto"}