2d:null 2e:["$","title",null,{"children":"2019 US Housing Values | Chris L Buie | Observable"}] 33:T51d,function sparkseesaw(data, options = {}) { let { width, height, margin } = { width: 125, height: 25, margin: { horizontal: .04, vertical: .125 }, ...options }; let series = d3 .stack() .keys(Object.keys(data[0])) .offset(d3.stackOffsetExpand)(data) .map(d => (d.forEach(v => (v.key = d.key)), d)); let x = d3 .scaleLinear() .range([width * margin.horizontal, width - width * margin.horizontal]); let y = d3 .scaleBand() .domain(data.map(d => d.name)) .range([height * margin.vertical, height - height * margin.vertical]); const svg = d3 .create("svg") .attr("width", width) .attr("height", height); const color = d3 .scaleOrdinal() .domain(series.map(d => d.key)) .range(['#c30000', 'rgb(254, 178, 76)']) .unknown("#ccc"); const bar = svg .selectAll("g") .data(data) .join("g") .attr("transform", (d, i) => `translate(${x(i)},0)`); svg .append("g") .selectAll("g") .data(series) .enter() .append("g") .attr("fill", d => color(d.key)) .selectAll("rect") .data(d => d) .join("rect") .attr("x", d => x(d[0])) .attr("y", (d, i) => y(d.data.name)) .attr("width", d => x(d[1]) - x(d[0])) .attr("height", y.bandwidth()); return svg.node(); }34:T87a,function stateValueTable(data, options = {}) { let { color, preset } = { color: "DarkSlateGray", preset: null, ...options }; if (window.innerWidth < 200) { preset = "mobile"; } let output = table( data.map( ({ Rank, Location, TotalHousingUnits, MedianValue, OwnerOccupiedUnits, LessThan50, V50to100, V100to150, V150to200, V200to300, V500to1MM, GreaterThan1MM }) => ({ Rank: md`${Rank}`, State: md`${Location}`, ['Total Housing Units (1M)']: md`${[ Math.round(TotalHousingUnits / 1000) ].toLocaleString("en-US")}`, ['Median Value (1M)']: md`${'$' + [Math.round(MedianValue / 1000)].toLocaleString("en-US")}`, ['$150M to $200M']: md`${V150to200.toString() + '%'}`, ['$200M to $300M']: md`${V200to300.toString() + '%'}`, ['$500M to $1MM']: md`${V500to1MM.toString() + '%'}`, // ['Renter Ratio']: sparkseesaw( // [ // { // Green: Math.round( // ((TotalHousingUnits - OwnerOccupiedUnits) / TotalHousingUnits) * // 100 // ), // Red: // 100 - // ((TotalHousingUnits - OwnerOccupiedUnits) / TotalHousingUnits) * // 100 // } // ], // (options = {}) // ), Distribution: bar( [ LessThan50, V50to100, V100to150, V150to200, V200to300, V500to1MM, GreaterThan1MM ], (options = { width: 125, height: 25, color: { fill: "rgb(254, 178, 76)", stroke: "white" }, highlights: { start: null, end: null, min: null, max: null }, datum: null, scaling: "min", margin: { horizontal: .04, vertical: .125 } }) ) }) ), { width: "100%", align: ["left", "center", "center", "center", "center", "center"] } ); return output; }35:[{"id":"9c947503e2debd69ccf4a9c9e67a44741dbc5698bed041228420c47d3753932ef1452c83412a6fdfa91a11b27ac581453008a081d2039ba3f7c479f5c81d7dcd","href":"https://static.observableusercontent.com/files/9c947503e2debd69ccf4a9c9e67a44741dbc5698bed041228420c47d3753932ef1452c83412a6fdfa91a11b27ac581453008a081d2039ba3f7c479f5c81d7dcd","name":"mapdata@5.csv","type":"text/csv","lastModified":1629752514602.045,"size":506524},{"id":"53d72c7b81f5c520d08961feed71576fb00dec882c2a1e968143b988978633f3d19343b29a04c2cfd4698366a505f102cd02259c430eaeb4ae6ec0eaf44bb0ab","href":"https://static.observableusercontent.com/files/53d72c7b81f5c520d08961feed71576fb00dec882c2a1e968143b988978633f3d19343b29a04c2cfd4698366a505f102cd02259c430eaeb4ae6ec0eaf44bb0ab","name":"2019ACSDPO4OwnerOccupiedHousingValueCutsPvt@4.csv","type":"text/csv","lastModified":1629835254483.351,"size":4301}] 31:{"id":"0ead6acbbfc9eabb","slug":"usa-housing-value","title":"2019 US Housing Values","thumbnail":"6aecc5e158edc816631c25062225c0daf3bcd510312401d0e69fdffb1ef00ad4","access_level":"public","create_time":"$D2021-08-20T20:33:45.359Z","update_time":"$D2021-09-02T20:44:36.081Z","view_time":null,"first_public_time":"$D2021-08-24T16:25:02.241Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"5ff335675a444f4e","login":"cbuie","name":"Chris L Buie","avatar_url":"https://avatars-next.observableusercontent.com/b68b101792a9b0a1bdd51d7424d01cd84dea6bd34ad829460c93e27aad96ebb2","tier":"starter_2024"},"version":786,"publish_version":786,"role":null,"authored":false,"authors":[{"type":"individual","id":"fb193f2e50e06492","login":"cbuie","name":"Chris L Buie","avatar_url":"https://avatars-next.observableusercontent.com/b68b101792a9b0a1bdd51d7424d01cd84dea6bd34ad829460c93e27aad96ebb2","tier":null}],"members":[{"type":"individual","id":"fb193f2e50e06492","login":"cbuie","name":"Chris L Buie","avatar_url":"https://avatars-next.observableusercontent.com/b68b101792a9b0a1bdd51d7424d01cd84dea6bd34ad829460c93e27aad96ebb2","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":{"id":"6ca00cfb1bc2455a","slug":"census","title":"Census","owner":{"id":"5ff335675a444f4e","login":"cbuie","name":"Chris L Buie"}},"type":"notebook","body":{"title":"2019 US Housing Values","cells":[{"id":738,"value":"md`# 2019 US Housing Values`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":703,"value":"md`#### Select Value Cut:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":251,"value":"viewof mapVariable = html`\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":0,"value":"md`## USA Housing Value`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":73,"value":"countyMap","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":635,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":613,"value":"md`## Units by Percentage of Value by State`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":733,"value":"md` The inline distribution below represents the percentage of each value cut displayed above, arranged from less than $50k to greater than $1MM`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":745,"value":"md` States ranked by highest percentage of units greater than $1MM.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":486,"value":"stateValueTable(z.addCol(\"Rank\", Array.from({ length: hv.length }, (v, k) => k + 1), hv))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":630,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":461,"value":"md` ### Summary Table Dependencies`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":600,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"hv = FileAttachment(\"2019ACSDPO4OwnerOccupiedHousingValueCutsPvt@4.csv\").csv({\n typed: true\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":468,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":466,"value":"import { bar, line, table } from \"@hamzaamjad/tiny-charts\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":453,"value":"md`### Map Dependencies`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":140,"value":"county_id = z.deriveCol(r => r.id.split('US')[1], dp04_county)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":143,"value":"map_variable = z.getCol(mapVariable, dp04_county)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":246,"value":"mapVariables = [\n { name: 'Per_Less_than_50000', label: \"Less than $50M (%)\" },\n { name: 'Per_units_50000_to_99999', label: \"$50M to $100M (%)\" },\n { name: 'Per_units_100000_to_149999', label: \"$100M to $150M (%)\" },\n { name: 'Per_units_150000_to_199999', label: \"$150M to $200M (%)\" },\n { name: 'Per_units_200000_to_299999', label: \"$200M to $300M (%)\" },\n { name: 'Per_units_300000_to_499999', label: \"$300M to $500M (%)\" },\n { name: 'Per_units_500000_to_999999', label: \"$500M to $1MM (%)\" },\n { name: 'Per_units_1000000_or_more', label: \"Greater than $1MM (%)\" }\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"import { chart as countyMap } with {\n mapData as data,\n color,\n mapLegend\n} from \"@cbuie/choropleth\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":299,"value":"import { legend } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"dp04_county = FileAttachment(\"mapdata@5.csv\").csv({\n typed: true\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":773,"value":"z.sortByCol(\"Geographic_Area_Name\", \"asc\", dp04_county)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":160,"value":"mapData = {\n let i = 0;\n let dataOut = [];\n for (i; i < county_id.length; i++) {\n dataOut.push([county_id[i], parseFloat(map_variable[i]).toFixed(1)]);\n }\n return Object.assign(new Map(dataOut), { title: mapVariable });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":75,"value":"color = d3.scaleQuantize([1, 50], d3.schemeYlOrRd[9])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":297,"value":"mapLegend = legend({\n color: d3.scaleQuantize([.1, .5], d3.schemeOrRd[9]),\n ticks: 10,\n width: 260,\n title: mapVariables.find(({ name }) => name === mapVariable).label,\n tickFormat: \"0.0%\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":627,"value":"md`### Imports`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":62,"value":"z = require('https://bundle.run/zebras@0.0.11')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":777,"value":"html`\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W35","stdlib":"1","titling":"auto"}} 32:"$31:body"