2f:T575,> from https://business.fau.edu/departments/finance/real-estate-initiative/housing-market-ranking/housing-top-100/ Using ZHVI scores, a simple Housing Index (HI) time trend can be developed from the primary data: ``` HIt = β0+β1xt+εt (I) ``` Here t represents the numeric month for data with t = 1 representing January 1996 and xt is a time trend code in terms of months. The HI estimation equation provides for the development of a fundamental long-term pricing trend based on over 25 years of data: ``` E(HIt) = β0+β1xt. (II) ``` Here E(HIt) is the expected HI or ZHVI. The degree that a local housing market is above or below its fundamental long-term pricing trend can then be calculated. Since the data is available monthly, the calculation is as follows: ``` Degree Above or Below Market Pricingt = ((Actual ZHVIt - E(HIt)) / (E(HIt)) (III) ``` Equation III is the percentage difference between where housing prices should be and the market’s actual scores at time t. Positive values for III represent a degree of overpricing while negative values represent a degree of underpricing.30:[{"id":"e5087a10dc70af8a874191f1778880ed2deabc11c00f0c1bbe8bc2fc7ffe7db292974a7502deb13d2654924a6ac47c1a1f82527f127a6467f37af4a186b34acb","href":"https://static.observableusercontent.com/files/e5087a10dc70af8a874191f1778880ed2deabc11c00f0c1bbe8bc2fc7ffe7db292974a7502deb13d2654924a6ac47c1a1f82527f127a6467f37af4a186b34acb","name":"redfin_2021-08-16-14-50-32.csv","type":"text/csv","lastModified":1629150831375.106,"size":53896},{"id":"f2f81e377071b0c7b03636949c545c0d8f62285a0656ba2e70a4fdf3737e896f83d748d3816c3ef8ba920e1d2db77eeeb4cbc9a2f61a6d787880ff275eddfcab","href":"https://static.observableusercontent.com/files/f2f81e377071b0c7b03636949c545c0d8f62285a0656ba2e70a4fdf3737e896f83d748d3816c3ef8ba920e1d2db77eeeb4cbc9a2f61a6d787880ff275eddfcab","name":"redfin_2021-08-16-18-02-02 - sqft desc.csv","type":"text/csv","lastModified":1629162304542.492,"size":123007}] 2d:{"title":"House Buying Analysis","cells":[{"id":0,"value":"md`# House Buying Analysis\n1. 👍 find,filter,inspect,and enhance the data for what we've searched for\n1. 👍 generate \"windows\" into our behavior\n1. 🔜 apply those windows to a 48h-5d \"recent houses\" to better pattern match. **needs a button/thing to fetch latest data for 48h and look at what sticks**\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":353,"value":"viewof cities = Inputs.checkbox(\n records.map((d) => d.CITY),\n {\n value: [\"Medford\", \"Melrose\", \"Winchester\", \"Malden\"],\n multiple: true,\n unique: true,\n label: \"Cities\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":641,"value":"## Explore\n\n***Note: filters apply to all charts***","pinned":false,"hidden":false,"mode":"md"},{"id":269,"value":"viewof maxLot = Inputs.range(d3.extent(records, d => d[\"LOT SIZE\"]), {\n value: 25000,\n step: 1000,\n label: \"Lot Size <=\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":628,"value":"viewof maxSF = Inputs.range(\n d3.extent(records, (d) => d[\"SQUARE FEET\"]),\n {\n value: 3000,\n step: 100,\n label: \"Square Ft <=\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":290,"value":"viewof maxCostSF = {\n const key = \"$/SQUARE FEET\";\n return Inputs.range(d3.extent(records, d => d[key]), {\n value: 1200,\n step: 10,\n label: \"$/SQUARE FEET <=\"\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":466,"value":"viewof oldestLookback = {\n const key = \"DAYS ON MARKET\";\n return Inputs.range(d3.extent(records, d => d[key]), {\n value: -200,\n step: 10,\n label: \"Days On Market >=\"\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":366,"value":"chart({ x, y, group })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1320,"value":"// dots: a listing on redfin, colored by town\n// black dots: our favorites\n// color blocks: grouping favorites by town","pinned":true,"hidden":false,"mode":"ojs"},{"id":569,"value":"viewof x = Inputs.select(numericKeys, {\n value: \"LOT SIZE\",\n unique: true,\n label: \"x-axis\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":581,"value":"viewof y = Inputs.select(numericKeys, {\n value: \"$/SQUARE FEET\",\n unique: true,\n label: \"y-axis\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":600,"value":"viewof group = Inputs.select(stringKeys, {\n value: \"CITY\",\n unique: true,\n label: \"color by\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":655,"value":"viewof values = Inputs.checkbox(\n records.map((d) => d[group]),\n {\n value: records.map((d) => d[group]),\n multiple: true,\n unique: true,\n label: \"Color Values\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1222,"value":"md`## House Value`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1235,"value":"md`> what's good house value?\n\nStrong correlation because $/sf and square footage is fairly obvious.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1223,"value":"chart({ x: \"SQUARE FEET\" }, { x: { tickFormat: \"d\" } })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1302,"value":"Plot.plot({\n x: { tickFormat: \"d\" },\n width,\n facet: {\n data,\n marginLeft: 100,\n y: \"CITY\"\n },\n color: {\n scheme: \"YlGnBu\"\n },\n marks: [\n Plot.barX(\n data,\n Plot.binX(\n { fill: \"proportion\" },\n { x: \"$/SQUARE FEET\", inset: 0.5, thresholds: 30 }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1305,"value":"Plot.plot({\n x: { tickFormat: \"d\" },\n width,\n facet: {\n data,\n marginLeft: 100,\n y: \"FAVORITE\"\n },\n color: {\n scheme: \"YlGnBu\"\n },\n marks: [\n Plot.barX(\n data,\n Plot.binX(\n { fill: \"proportion-facet\" },\n { x: \"$/SQUARE FEET\", inset: 0.5, thresholds: 30 }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1238,"value":"notice(md`our sweet spot is \\`1600 <= sf <= 2200\\` and \\`<= $475/sf\\``)","pinned":false,"hidden":false,"mode":"ojs"},{"id":61,"value":"{\n const x = timeline,\n y = \"$/SQUARE FEET\",\n d = data.filter(({ \"SOLD DATE\": year }) =>\n dfns.isAfter(year, new Date(2020, 8, 1))\n );\n\n return html`${key()}${Plot.plot({\n grid: true,\n inset: 10,\n x: {\n type: timeline === \"DAYS ON MARKET\" ? \"linear\" : \"time\"\n },\n width,\n marks: [\n Plot.dot(d, {\n x,\n y,\n r: 2\n }),\n Plot.lineY(\n d,\n Plot.groupX(\n { y: \"mean\" },\n {\n x: x.includes(\"DATE\") ? binMonthlyBy(x) : binCount(x),\n y,\n z: \"CITY\",\n // curve: \"natural\",\n strokeWidth: 2,\n stroke: \"CITY\"\n }\n )\n )\n ]\n })}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1160,"value":"viewof timeline = Inputs.radio([\"DAYS ON MARKET\", \"SOLD DATE\"], {\n value: \"SOLD DATE\",\n label: \"x-axis:\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1150,"value":"binCount = key => d => Math.floor(d[key] / 15) * 15","pinned":false,"hidden":false,"mode":"ojs"},{"id":1115,"value":"binMonthlyBy = key => ({ [key]: d }) =>\n dfns.set(dfns.parse(dfns.format(d, \"y-M\"), \"y-M\", new Date()), {\n date: 15\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":620,"value":"## Housing Age","pinned":false,"hidden":false,"mode":"md"},{"id":554,"value":"> is there a majority of old houses in one city or another?\n\nWinchester skews newer and Medford a little older but short answer: **not really**.","pinned":false,"hidden":false,"mode":"md"},{"id":389,"value":"Plot.plot({\n x: { tickFormat: \"d\" },\n width,\n facet: {\n data,\n marginLeft: 100,\n y: \"CITY\"\n },\n color: {\n scheme: \"YlGnBu\"\n },\n marks: [\n Plot.barX(\n data,\n Plot.binX(\n { fill: \"proportion\" },\n { x: \"YEAR BUILT\", inset: 0.5, thresholds: 30 }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":381,"value":"chart({ x: \"YEAR BUILT\" }, { x: { tickFormat: \"d\" }, thresholds: 20 })","pinned":false,"hidden":false,"mode":"ojs"},{"id":688,"value":"md`## Mapping / Transit / Access`","pinned":false,"hidden":false,"mode":"ojs"},{"id":987,"value":"> where are the houses with greater access to transit?\n\nMelrose & some of Malden – you can see just how much of Medford lacks access to easy transit. This is also a little skewed, as we know that West Medford will have subway access in the coming year.","pinned":false,"hidden":false,"mode":"md"},{"id":934,"value":"Plot.plot({\n x: { tickFormat: \"~s\" },\n width,\n facet: {\n data,\n marginLeft: 100,\n y: \"CITY\"\n },\n color: {\n scheme: \"YlGnBu\"\n },\n marks: [\n Plot.barX(\n data,\n Plot.binX(\n { fill: \"proportion\" },\n { x: \"CLOSEST STOP\", inset: 0.5, thresholds: 30 }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":939,"value":"Plot.plot({\n x: { tickFormat: \"~s\" },\n width,\n facet: {\n data,\n marginLeft: 100,\n y: \"FAVORITE\"\n },\n color: {\n scheme: \"YlGnBu\"\n },\n marks: [\n Plot.barX(\n data,\n Plot.binX(\n { fill: \"proportion-facet\" },\n { x: \"CLOSEST STOP\", inset: 0.5, thresholds: 30 }\n )\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1211,"value":"notice(\n md`unsurprisingly, our favorites cluster below ¾ mile from a train station`\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":88,"value":"{\n // const x = \"DAYS ON MARKET\";\n const x = \"LOT SIZE\";\n const y = \"CLOSEST STOP\";\n const d = data;\n\n return Plot.plot({\n height: 600,\n width,\n grid: true,\n x: { ticks: 5, tickFormat: \"~s\" },\n facet: {\n data: d,\n x: \"FAVORITE\",\n y: \"CITY\",\n marginRight: 80\n },\n marks: [\n Plot.frame(),\n Plot.dot(d.slice(), {\n x,\n y,\n r: 1,\n fill: \"#ddd\"\n }),\n Plot.dot(d, {\n x,\n y,\n z: \"FAVORITE\",\n stroke: \"FAVORITE\",\n r: 2\n })\n ]\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":697,"value":"### train / subway stops","pinned":false,"hidden":false,"mode":"md"},{"id":702,"value":"- docs: https://api-v3.mbta.com/docs/swagger/index.html\n- example: https://api-v3.mbta.com/stops?filter[route_type]=0,1,2,4\n - filtered per: https://developers.google.com/transit/gtfs/reference#routestxt","pinned":false,"hidden":false,"mode":"md"},{"id":873,"value":"fetchStops = memoize(() =>\n fetch(`https://api-v3.mbta.com/stops?filter[route_type]=0,1,2,4`)\n .then(resp => resp.json())\n .then(json => json.data)\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":735,"value":"stops = fetchStops()","pinned":false,"hidden":false,"mode":"ojs"},{"id":706,"value":"### map resources\n> see also MBTA [route explorer]\n\n* [turf.js](https://turfjs.org/) for analysis/utilities\n* future: [deck.gl](https://observablehq.com/@pessimistress?tab=notebooks&type=public) for visualization\n* [mbta api]\n* [mbta viz]\n\n[mbta api]: https://www.mbta.com/developers/v3-api\n[mbta viz]: http://mbtaviz.github.io/\n[route explorer]: https://observablehq.com/d/bae3b8760366930a","pinned":false,"hidden":false,"mode":"md"},{"id":748,"value":"/* Memoized - the distance between two points will never change.\n- a: [long,lat]\n- b: [long,lat]\n*/\ngetDistance = memoize((a, b) => turf.distance(a, b, { units: \"miles\" }))","pinned":true,"hidden":false,"mode":"ojs"},{"id":771,"value":"viewof sample = Inputs.table(data, {\n required: false,\n format: {\n \"URL (SEE http://www.redfin.com/buy-a-home/comparative-market-analysis FOR INFO ON PRICING)\": u =>\n html`${u}`\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":777,"value":"sample.length === 2\n ? getDistance(...sample.map(r => [r.LONGITUDE, r.LATITUDE]))\n : \"select two points in table above to see the distance between them\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1340,"value":"## Over/Under-price Analysis","pinned":false,"hidden":false,"mode":"md"},{"id":1343,"value":"$2f","pinned":false,"hidden":false,"mode":"md"},{"id":538,"value":"## Appendix","pinned":false,"hidden":false,"mode":"md"},{"id":1009,"value":"**charting**","pinned":false,"hidden":false,"mode":"md"},{"id":924,"value":"key = () => Swatches({\n color: d3.scaleOrdinal(data.map(d => d[group]).sort(), d3.schemeTableau10)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"chart = (\n { x = \"LOT SIZE\", y = \"$/SQUARE FEET\", group = \"CITY\", bin } = {},\n options\n) => {\n const defaults = { x: {}, thresholds: 10 };\n options = Object.assign({}, defaults, options);\n\n return html`${key()}${Plot.plot({\n x: options.x,\n width,\n height: 600,\n marks: [\n // bins\n Plot.rect(\n data.filter((d) => d.FAVORITE === \"Y\"),\n Plot.bin(\n { fillOpacity: \"count\" },\n { x, y, fill: group, thresholds: options.thresholds }\n )\n ),\n Plot.dot(data, {\n x,\n y,\n r: 2,\n stroke: group\n }),\n Plot.dot(\n data.filter((d) => d.FAVORITE === \"Y\"),\n {\n x,\n y,\n r: 2,\n fill: \"black\"\n }\n )\n ]\n })}${Plot.rectY(\n data,\n Plot.binX(\n { y: \"count\" },\n { x, fill: group, thresholds: options.thresholds }\n )\n ).plot({ width, height: 100, x: options.x })}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":152,"value":"import { swatches as Swatches } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":870,"value":"**data**","pinned":false,"hidden":false,"mode":"md"},{"id":2,"value":"// raw input\ninput = FileAttachment(\"redfin_2021-08-16-18-02-02 - sqft desc.csv\").csv({\n typed: true\n})\n// FileAttachment(\"redfin_2021-08-16-14-50-32.csv\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":883,"value":"/**\nEnhance the base data:\n - adds \"CLOSEST STOP\" for proximity to subway etc\n - updates \"DAYS ON MARKET\" to be a negative offset from 0 (more negative = older)\n - updates \"SOLD DATE\" to be a true date object\n**/\nenhanceInput = (e, i, arr) => {\n const house = { ...e };\n house[\"SOLD DATE\"] =\n house[\"SOLD DATE\"] === null ? null : parseDateRedfin(house[\"SOLD DATE\"]); //August-6-2021\n house[\"DAYS ON MARKET\"] *= -1;\n house[\"CLOSEST STOP\"] = Math.min(\n ...stops.map(({ attributes: stop }) =>\n getDistance(\n [stop.longitude, stop.latitude],\n [house.LONGITUDE, house.LATITUDE]\n )\n )\n );\n\n return house;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":892,"value":"// input, enhanced (do once)\nrecords = input.map(enhanceInput)","pinned":true,"hidden":false,"mode":"ojs"},{"id":108,"value":"data = records.filter(\n row =>\n values.includes(row[group]) &&\n row[\"SQUARE FEET\"] <= maxSF &&\n row[\"LOT SIZE\"] <= maxLot &&\n row[\"$/SQUARE FEET\"] <= maxCostSF &&\n cities.includes(row.CITY) &&\n row[\"DAYS ON MARKET\"] >= oldestLookback\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":595,"value":"stringKeys = Object.keys(records[0]).filter(\n (k) => typeof records[0][k] === \"string\"\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":593,"value":"numericKeys = Object.keys(records[0]).filter(\n (k) => typeof records[0][k] === \"number\" || k.includes(\"DATE\")\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":859,"value":"**mapping**","pinned":false,"hidden":false,"mode":"md"},{"id":750,"value":"turf = require(\"@turf/turf\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":862,"value":"**UI**","pinned":false,"hidden":false,"mode":"md"},{"id":1208,"value":"import { notice } from \"@sgregson/components\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":558,"value":"import { styles } from \"@sgregson/styles\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":560,"value":"styles","pinned":false,"hidden":false,"mode":"ojs"},{"id":1003,"value":"**utils**","pinned":false,"hidden":false,"mode":"md"},{"id":1046,"value":"parseDateRedfin = (input) => dfns.parse(input, \"MMMM-d-y\", new Date())","pinned":true,"hidden":false,"mode":"ojs"},{"id":1036,"value":"dfns = require(\"https://bundle.run/date-fns@2.14.0\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":827,"value":"//cache by stringifying args\nmemoize = R.memoizeWith(function() {\n return JSON.stringify(flatObj(arguments));\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":811,"value":"function flatObj(obj, prefix = \"\") {\n return Object.keys(obj).reduce((acc, k) => {\n const pre = prefix.length ? prefix + \".\" : \"\";\n if (typeof obj[k] === \"object\")\n Object.assign(acc, flatObj(obj[k], pre + k));\n else acc[pre + k] = obj[k];\n return acc;\n }, {});\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":754,"value":"R = require(\"ramda\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":692,"value":"import { localStorage } from \"@mbostock/safe-local-storage\";","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W30","stdlib":"1","titling":"auto"}