32:T8c7,map = { let h = (width<600) ? width + 200: width * 0.75, z = (width<600) ? 6.5 : 7, container = DOM.element('div', { style: `width:${width}px;height:${h}px` }); yield container; let map = L.map(container).setView([44.6,-69.0], z); let osmLayer = L.tileLayer('https://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}@2x.png', { attribution: '© OpenStreetMap contributors' }).addTo(map); L.TopoJSON = L.GeoJSON.extend({ addData: function (data) { var geojson, key; if (data.type === "GeometryCollection") { for (key in data.objects) { if (data.objects.hasOwnProperty(key)) { geojson = topojson.feature(data, data.objects[key]); L.GeoJSON.prototype.addData.call(this, geojson); } } return this; } L.GeoJSON.prototype.addData.call(this, data); return this; } }); L.topoJson = function (data, options) { return new L.TopoJSON(data, options); }; //create an empty geojson layer //with a style and a popup on click let overlay = L.topoJson(zips, { style: function(feature) { let zip =feature.properties.ZCTA5CE10, dat = getDataForFeature(zip, 'rebates'), c = dat ? colorRamp(dat) : '#fff', o = dat ? 1 : 0; return { color : c, stroke: '#999', opacity: 1, weight: 0.5, fillOpacity: o } }, onEachFeature: function(feature, layer) { let rebates = getDataForFeature(feature.properties.ZCTA5CE10, 'rebates') ? getDataForFeature(feature.properties.ZCTA5CE10, 'rebates') : 0, count = getDataForFeature(feature.properties.ZCTA5CE10, 'count') ? getDataForFeature(feature.properties.ZCTA5CE10, 'count') : 0, s = (count==1) ? '' : 's'; layer.bindPopup('

ZIP code '+feature.properties.ZCTA5CE10+'

Subsidies paid: $'+rebates+' for ' + count + ' car' + s +'

') } }).addTo(map); let legend = L.control({position: 'topleft'}) legend.onAdd = function (map) {var div = L.DomUtil.create('div', 'legend'); return l}; legend.addTo(map); }33:[{"id":"f1f6320b0a915b6b9394eb16bbefdfda9b3da9eb9b8ad854c34c872817beba8c96ebd515cc02248257bc890a4feb701b8357c9e41829f07c04f259e3b0d76a55","href":"https://static.observableusercontent.com/files/f1f6320b0a915b6b9394eb16bbefdfda9b3da9eb9b8ad854c34c872817beba8c96ebd515cc02248257bc890a4feb701b8357c9e41829f07c04f259e3b0d76a55","name":"EV_Rebates_04.14.2020@3.csv","type":"text/csv","lastModified":1588173656844.628,"size":2056}] 30:{"title":"Maine's electric car subsidies mostly benefit wealthier coastal communities","cells":[{"id":0,"value":"md`# Maine's electric car subsidies mostly benefit wealthier coastal communities\n\nIn the 7.5 months between August 29, 2019 and April 20, 2020, Efficiency Maine spent $691,000 to subsidize the purchase of 403 new electric vehicles in Maine.\n\nTo put that number into some context, for the entire fiscal year 2019, the State of Maine spent only $170,000 to support the [Greater Portland METRO transit agency](https://gpmetro.org/179/FINANCIAL-INFORMATION), the state's biggest public transit provider.\n\nThe majority of the state's EV subsidies have gone to individual car buyers in relatively wealthy coastal communities, particularly in Cumberland and York Counties, according to an analysis of rebate ZIP codes, mapped below.\n\nMaine has about 1 million registered passenger vehicles; these 400 new electric cars make up one twenty-fifth of one percent of the state's entire passenger vehicle fleet. \n\n\n\n\n\nData courtesy of Efficiency Maine.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":19,"value":"$32","pinned":true,"hidden":false,"mode":"ojs"},{"id":4,"value":"L = require('leaflet@1.2.0')","pinned":true,"hidden":false,"mode":"ojs"},{"id":6,"value":"html``","pinned":true,"hidden":false,"mode":"ojs"},{"id":37,"value":"topojson = require(\"topojson-client@3\")\n","pinned":true,"hidden":false,"mode":"ojs"},{"id":11,"value":"zips = {\n let response = await fetch('https://gist.githubusercontent.com/vigorousnorth/d1cb350a6cbb8bdc54be64d9698ba3aa/raw/6cec88320aeaeed9386f14083ae4ed2629f380dd/MaineZCTAs_topo.json');\n let json = await response.json();\n return topojson.feature(json, json.objects.zipsNAD83)\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":92,"value":"data = {\n let raw = await FileAttachment(\"EV_Rebates_04.14.2020@3.csv\").text();\n return d3.csvParse(raw, (d) => { d.rebates = +d.rebates; d.count = +d.count; return d; })\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":102,"value":"getDataForFeature = (d, key) => {\n let a = false;\n for (let i = 0; i < data.length; i++) {\n if (d == data[i].zip) { a = data[i][key]; break; }\n else { continue }\n }\n return a;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":106,"value":"import {legend} from \"@d3/color-legend\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":111,"value":"colorRamp = d3.scaleLinear()\n .domain([0, 10000, 40000])\n .range([\"#fdd0a2\", \"#d94801\",\"#88419d\"])","pinned":true,"hidden":false,"mode":"ojs"},{"id":108,"value":"l = legend({\n color: colorRamp,\n width: (width<500) ? width*0.6:320,\n title: \"New car subsidies per ZIP code\", \n tickFormat: \"$0s\"\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":95,"value":"d3 = require('d3@5.0')\n","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}