30:Tb68,embed = html`

${ categorizedData.get('Federal')[0].office }	${d3.format( ',' )( allDataClean .get(response.normalizedInput.state) .get("US President") .get("statewide") .get(2016).movVotes )} votes	${ cookPrez.find( d => states.get(d.State) === response.normalizedInput.state )['Cook Rating'] }	+${d3.format(".2%")( pollsPrezAvgClean.get(statesRev.get(response.normalizedInput.state)) .movEstimate / 100 )}
${ pollsPrezAvgClean.get(statesRev.get(response.normalizedInput.state)) .leader }
${ pollsPrezAvgClean.get(statesRev.get(response.normalizedInput.state)) .follower }

${ categorizedData.get('Federal')[2].office }	${ categorizedData.get('Federal')[2].politicians[0].name } ${partyColor( categorizedData.get('Federal')[2].politicians[0].party[0] )}

${ categorizedData.get('Federal')[2].office }	${ categorizedData.get('Federal')[2].politicians[1].name } ${partyColor( categorizedData.get('Federal')[2].politicians[1].party[0] )}

${response.offices .find(d => d.name === "U.S. Representative") .divisionId.slice(-2)}${ categorizedData.get('Federal')[3].office }	${d3.format(',')( allDataClean .get(response.normalizedInput.state) .get("US House") .get( +response.offices .find(d => d.name === "U.S. Representative") .divisionId.slice(-2) ) .get(2018).movVotes )} votes${categorizedData .get('Federal')[3] .politicians.map( d => html`${d.name} ${partyColor(d.party[0])} ` )}

`31:T4bd,clean = { const parser = d3.utcParse('%m/%d/%Y'); const parsed = pollsPrezAvgRaw.map( d => new Object({ ...d, modeldate: parser(d.modeldate) }) ); const filtered = parsed .filter( d => new Date(d.modeldate).getDate() === new Date().getDate() - 1 && new Date(d.modeldate).getMonth() === new Date().getMonth() && new Date(d.modeldate).getYear() === new Date().getYear() ) .slice() .sort( (a, b) => d3.ascending(a.state, b.state) || d3.descending(a.modeldate, b.modeldate) || d3.descending(a.pct_trend_adjusted, b.pct_trend_adjusted) ); const grouped = d3.rollup( filtered, v => d3.pairs( v, (a, b) => new Object({ leader: a.candidate_name, follower: b.candidate_name, leaderEstimate: a.pct_estimate, followerEstimate: b.pct_estimate, leaderAdjusted: a.pct_trend_adjusted, followerAdjusted: b.pct_trend_adjusted, movEstimate: a.pct_estimate - b.pct_estimate, movAdjusted: a.pct_trend_adjusted - b.pct_trend_adjusted }) )[0], d => d.state ); return filtered; }32:[{"id":"95affa81b2d15e22a152dbbc931f75c2320a8558ec5c1f6d2c2adaa4d4b00d5dbb236db7e0fddcde8e644f268d956d4153adf20c3c5d5bc1a2bb4b6006eefceb","href":"https://static.observableusercontent.com/files/95affa81b2d15e22a152dbbc931f75c2320a8558ec5c1f6d2c2adaa4d4b00d5dbb236db7e0fddcde8e644f268d956d4153adf20c3c5d5bc1a2bb4b6006eefceb","name":"cookPVI.csv","type":"text/csv","lastModified":1592359743609.009,"size":20555},{"id":"6839e0dbd67f90d27e936c499beac86df589e461267933ee7752edc20dd4bf716d7481ed90520d2a6027de8ffedf3e660c110f4b6a9126f5bb4d8fa2b39b4638","href":"https://static.observableusercontent.com/files/6839e0dbd67f90d27e936c499beac86df589e461267933ee7752edc20dd4bf716d7481ed90520d2a6027de8ffedf3e660c110f4b6a9126f5bb4d8fa2b39b4638","name":"U.S. Senate-Cook U.S. Senate Ratings - 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Target-DCCC Target Districts 2020.csv","type":"text/csv","lastModified":1592369364217.353,"size":2303},{"id":"39a9c3e5980cb1e1f47e9f34e58c6b1e38c898adfeddbd2a5170e97dfebdbf466011c138aa0d903b03dbedef2197b42b869118f7b7d2e105245b8d028065ed07","href":"https://static.observableusercontent.com/files/39a9c3e5980cb1e1f47e9f34e58c6b1e38c898adfeddbd2a5170e97dfebdbf466011c138aa0d903b03dbedef2197b42b869118f7b7d2e105245b8d028065ed07","name":"DCCC - Red to Blue-DCCC Initial Red to Blue 2020@1.csv","type":"text/csv","lastModified":1592370125995.181,"size":1318},{"id":"211eda0097cec843f0a54e3f02d0fa5c6bbce576e15bf4a92080496a8ff43f39ebf2262b8f635039f241dd3ac974a85f122067e96b576d639d19fb6ba7dc309a","href":"https://static.observableusercontent.com/files/211eda0097cec843f0a54e3f02d0fa5c6bbce576e15bf4a92080496a8ff43f39ebf2262b8f635039f241dd3ac974a85f122067e96b576d639d19fb6ba7dc309a","name":"Governors-Cook Governor Ratings - April 3, 2020.csv","type":"text/csv","lastModified":1592362671808.477,"size":392},{"id":"5706a61a94755fa34511210c6003a8d0b371408968508fde0e7ec601e3349c7a7bd7b98103af9f0e2d7793c1e4466af3f5b43615f31ff4a4c269be20e887dcd2","href":"https://static.observableusercontent.com/files/5706a61a94755fa34511210c6003a8d0b371408968508fde0e7ec601e3349c7a7bd7b98103af9f0e2d7793c1e4466af3f5b43615f31ff4a4c269be20e887dcd2","name":"DCCC - Initial Frontline-DCCC Initial Frontline Candidates 2020.csv","type":"text/csv","lastModified":1592369364222.893,"size":2200},{"id":"2af8394e97949e79244bc50f12965c4ca8a1b8e8c24357326a39f2bdacea773762e1de41982a0e3a7f63fa0893954665807ab9de53e38ea53803ff8257435536","href":"https://static.observableusercontent.com/files/2af8394e97949e79244bc50f12965c4ca8a1b8e8c24357326a39f2bdacea773762e1de41982a0e3a7f63fa0893954665807ab9de53e38ea53803ff8257435536","name":"NRCC - Young Guns (Radar)-NRCC Young Guns (On the Radar) 2020.csv","type":"text/csv","lastModified":1592399489250.533,"size":2771},{"id":"49b830c8f60f7ac9c146e750b7ce3a1d3c46db62e8f41e50095a3c6756cf83b351ea6282b4b19db70e664c959131e9989d25876a38065a264c09c29a4724d511","href":"https://static.observableusercontent.com/files/49b830c8f60f7ac9c146e750b7ce3a1d3c46db62e8f41e50095a3c6756cf83b351ea6282b4b19db70e664c959131e9989d25876a38065a264c09c29a4724d511","name":"NRCC - Patriot Program-NRCC Patriot Program.csv","type":"text/csv","lastModified":1592399489228.948,"size":1271},{"id":"81a13d0c7de0b7af33dcc5c35b36a6ccbfbed00b63ba9c12325752ddc496281e3bb4062d1dad77de8342aa9877b2f2a879850e6b3fd0a2c401d105da6e07d840","href":"https://static.observableusercontent.com/files/81a13d0c7de0b7af33dcc5c35b36a6ccbfbed00b63ba9c12325752ddc496281e3bb4062d1dad77de8342aa9877b2f2a879850e6b3fd0a2c401d105da6e07d840","name":"NRCC - Initial Target-NRCC Initial Target Districts 2020.csv","type":"text/csv","lastModified":1592399489257.011,"size":2803},{"id":"3426bc0bcf1d0b60de13d1c4f1d72f839c248a154460b134eacfdd4020a866798ab987a89a42cc9eabc9167abdaa703c10c5bae4d64617abc32c00c44a8f02f3","href":"https://static.observableusercontent.com/files/3426bc0bcf1d0b60de13d1c4f1d72f839c248a154460b134eacfdd4020a866798ab987a89a42cc9eabc9167abdaa703c10c5bae4d64617abc32c00c44a8f02f3","name":"Sheet 1-States.csv","type":"text/csv","lastModified":1592403794280.443,"size":689}] 2e:{"title":"Folding in Data","cells":[{"id":0,"value":"md`# Folding in Data`","pinned":false,"hidden":false,"mode":"ojs"},{"id":490,"value":"response","pinned":true,"hidden":false,"mode":"ojs"},{"id":178,"value":"md`### Cook Ratings`","pinned":false,"hidden":false,"mode":"ojs"},{"id":138,"value":"viewof solid = slider({\n title: 'Solid',\n min: 0,\n max: 5,\n step: 1,\n value: 0\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":74,"value":"viewof likely = slider({\n title: 'Likely',\n min: 0,\n max: 5,\n step: 1,\n value: 1\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":77,"value":"viewof lean = slider({\n title: 'Lean',\n min: 0,\n max: 5,\n step: 1,\n value: 2\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":85,"value":"viewof tossup = slider({\n title: 'Tossup',\n name: 'Democratic Tossup',\n min: 0,\n max: 5,\n step: 1,\n value: 3\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":184,"value":"md`### DCCC & NRCC Ratings`","pinned":false,"hidden":false,"mode":"ojs"},{"id":254,"value":"md`### Election Importance`","pinned":false,"hidden":false,"mode":"ojs"},{"id":256,"value":"viewof federal = slider({\n title: 'Presidential',\n min: 0,\n max: 100,\n step: 1,\n value: 90\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":257,"value":"viewof usSenate = slider({\n title: 'U.S. Senate',\n min: 0,\n max: 100,\n step: 1,\n value: 70\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":268,"value":"viewof usHouse = slider({\n title: 'U.S. House',\n min: 0,\n max: 100,\n step: 1,\n value: 50\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":272,"value":"viewof state = slider({\n title: 'State',\n min: 0,\n max: 100,\n step: 1,\n value: 30\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":277,"value":"viewof local = slider({\n title: 'Local',\n min: 0,\n max: 100,\n step: 1,\n value: 10\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":327,"value":"viewof address = text({\n title: \"Home Address\",\n placeholder: \"123 Political Way\",\n description: \"Without a congressional district, it will ERROR!\",\n submit: \"Let's Code!\",\n width: width,\n value: \"Lebanon, Kansas 66952\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":340,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":172,"value":"data = md`

\n## Datasets`","pinned":false,"hidden":false,"mode":"ojs"},{"id":584,"value":"pollsPrezAvgClean = d3.rollup(\n clean\n .slice()\n .sort(\n (a, b) =>\n d3.ascending(a.state, b.state) ||\n d3.descending(a.modeldate, b.modeldate) ||\n d3.descending(a.pct_trend_adjusted, b.pct_trend_adjusted)\n ),\n v =>\n d3.pairs(\n v,\n (a, b) =>\n new Object({\n leader: a.candidate_name,\n follower: b.candidate_name,\n leaderEstimate: a.pct_estimate,\n followerEstimate: b.pct_estimate,\n leaderAdjusted: a.pct_trend_adjusted,\n followerAdjusted: b.pct_trend_adjusted,\n movEstimate: a.pct_estimate - b.pct_estimate,\n movAdjusted: a.pct_trend_adjusted - b.pct_trend_adjusted\n })\n )[0],\n d => d.state\n // d => d.modeldate\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":620,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":571,"value":"pollsPrezAvgRaw = d3.csv(\n await 'https://projects.fivethirtyeight.com/2020-general-data/presidential_poll_averages_2020.csv',\n d3.autoType\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":812,"value":"style = html` `","pinned":true,"hidden":false,"mode":"ojs"},{"id":789,"value":"spark(\n Array.from(\n allDataClean\n .get(\"FL\")\n .get(\"US President\")\n .get(\"statewide\")\n ).map(d => d[1].movPercent)\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":798,"value":"Array.from(\n allDataClean\n .get(\"FL\")\n .get(\"US President\")\n .get(\"statewide\")\n).map(d => -d[1].movPercent)","pinned":true,"hidden":false,"mode":"ojs"},{"id":498,"value":"allDataClean = d3.rollup(\n allDataRaw\n .slice()\n .sort(\n (a, b) =>\n d3.ascending(a.state, b.state) ||\n d3.ascending(a.office, b.office) ||\n d3.ascending(a.district, b.district) ||\n d3.descending(a.year, b.year) ||\n d3.descending(a.candidatevotes, b.candidatevotes)\n )\n .map(\n d =>\n new Object({\n ...d,\n percent: d.candidatevotes / d.totalvotes\n })\n ),\n v =>\n d3.pairs(\n v,\n (a, b) =>\n new Object({\n firstCandidate: a.candidate,\n firstParty: a.party,\n firstVotes: a.candidatevotes,\n secondCandidate: b.candidate,\n secondParty: b.party,\n secondVotes: b.candidatevotes,\n movPercent: (a.percent - b.percent) * 100,\n movVotes: a.candidatevotes - b.candidatevotes,\n totalVotes: a.totalvotes\n })\n )[0],\n d => d.state_po,\n d => d.office,\n d => d.district,\n d => d.year\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":493,"value":"allDataRaw = d3.json(\n 'https://raw.githubusercontent.com/colanderworld/observable-datasets/master/MEDSLDataCombined.json'\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":187,"value":"md`### [Cook Political Report](https://cookpolitical.com/ratings)\n\n* Presidential\n* U.S. Senate\n* U.S. House\n* Governor\n* Partisan Voting Index (PVI)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":220,"value":"cookPrez = d3\n .csvParse(\n await FileAttachment(\n \"President-Cook U.S. Presidential Ratings - Mar 9, 2020.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': weight(d['Cook Rating'])\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":44,"value":"cookSenate = d3\n .csvParse(\n await FileAttachment(\n \"U.S. Senate-Cook U.S. Senate Ratings - June 12, 2020.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': weight(d['Cook Rating'])\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":39,"value":"cookHouse = d3\n .csvParse(\n await FileAttachment(\n \"U.S. House-Cook U.S. House Ratings - June 16, 2020.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': weight(d['Cook Rating'])\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":48,"value":"cookGovernor = d3\n .csvParse(\n await FileAttachment(\n \"Governors-Cook Governor Ratings - April 3, 2020.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': weight(d['Cook Rating'])\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"cookPVI = d3\n .csvParse(await FileAttachment(\"cookPVI.csv\").text(), d3.autoType)\n .map(\n d =>\n new Object({\n ...d,\n PVI: d.PVI[0] === \"R\" ? +-d.PVI.slice(2) : +d.PVI.slice(2)\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":190,"value":"md`### [DCCC](https://ballotpedia.org/Democratic_Congressional_Campaign_Committee)\n* Target\n* Frontline\n* Red to Blue`","pinned":false,"hidden":false,"mode":"ojs"},{"id":230,"value":"dcccTarget = d3\n .csvParse(\n await FileAttachment(\"DCCC - Target-DCCC Target Districts 2020.csv\").text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d\n })\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': \"Special SAUCE!\",\n '2018 Margin':\n d['2018 Margin'][0] === \"R\"\n ? +-d['2018 Margin'].slice(2)\n : +d['2018 Margin'].slice(2),\n '2016 Margin':\n d['2016 Margin'][0] === \"R\"\n ? +-d['2016 Margin'].slice(2)\n : +d['2016 Margin'].slice(2),\n '2014 Margin':\n d['2014 Margin'][0] === \"R\"\n ? +-d['2014 Margin'].slice(2)\n : +d['2014 Margin'].slice(2)\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":236,"value":"dcccFrontline = d3\n .csvParse(\n await FileAttachment(\n \"DCCC - Initial Frontline-DCCC Initial Frontline Candidates 2020.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': \"Special SAUCE!\",\n '2018 Margin':\n d['2018 Margin'][0] === \"R\"\n ? +-d['2018 Margin'].slice(2)\n : +d['2018 Margin'].slice(2),\n '2016 Margin':\n d['2016 Margin'][0] === \"R\"\n ? +-d['2016 Margin'].slice(2)\n : +d['2016 Margin'].slice(2),\n '2014 Margin':\n d['2014 Margin'][0] === \"R\"\n ? +-d['2014 Margin'].slice(2)\n : +d['2014 Margin'].slice(2)\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":227,"value":"dcccRedToBlue = d3\n .csvParse(\n await FileAttachment(\n \"DCCC - Red to Blue-DCCC Initial Red to Blue 2020@1.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': \"Special SAUCE!\",\n '2018 Margin':\n d['2018 Margin'][0] === \"R\"\n ? +-d['2018 Margin'].slice(2)\n : +d['2018 Margin'].slice(2),\n '2016 Margin':\n d['2016 Margin'][0] === \"R\"\n ? +-d['2016 Margin'].slice(2)\n : +d['2016 Margin'].slice(2),\n '2014 Margin':\n d['2014 Margin'][0] === \"R\"\n ? +-d['2014 Margin'].slice(2)\n : +d['2014 Margin'].slice(2)\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":193,"value":"md`### [NRCC](https://ballotpedia.org/National_Republican_Congressional_Committee) \n* Target\n* Young Guns (Radar)\n* Patriot Program`","pinned":false,"hidden":false,"mode":"ojs"},{"id":306,"value":"rnccTarget = d3\n .csvParse(\n await FileAttachment(\n \"NRCC - Initial Target-NRCC Initial Target Districts 2020.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': \"Special SAUCE!\",\n '2018 Margin':\n d['2018 Margin'][0] === \"R\"\n ? +-d['2018 Margin'].slice(2)\n : +d['2018 Margin'].slice(2),\n '2016 Margin':\n d['2016 Margin'][0] === \"R\"\n ? +-d['2016 Margin'].slice(2)\n : +d['2016 Margin'].slice(2),\n '2014 Margin':\n d['2014 Margin'][0] === \"R\"\n ? +-d['2014 Margin'].slice(2)\n : +d['2014 Margin'].slice(2)\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":310,"value":"rnccYoungGuns = d3\n .csvParse(\n await FileAttachment(\n \"NRCC - Young Guns (Radar)-NRCC Young Guns (On the Radar) 2020.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': \"Special SAUCE!\",\n '2018 Margin':\n d['2018 Margin'][0] === \"R\"\n ? +-d['2018 Margin'].slice(2)\n : +d['2018 Margin'].slice(2),\n '2016 Margin':\n d['2016 Margin'][0] === \"R\"\n ? +-d['2016 Margin'].slice(2)\n : +d['2016 Margin'].slice(2),\n '2014 Margin':\n d['2014 Margin'][0] === \"R\"\n ? +-d['2014 Margin'].slice(2)\n : +d['2014 Margin'].slice(2)\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":315,"value":"rnccPatriots = d3\n .csvParse(\n await FileAttachment(\n \"NRCC - Patriot Program-NRCC Patriot Program.csv\"\n ).text(),\n d3.autoType\n )\n .map(\n d =>\n new Object({\n ...d,\n 'Our Rating': \"Special SAUCE!\",\n '2018 Margin':\n d['2018 Margin'][0] === \"R\"\n ? +-d['2018 Margin'].slice(2)\n : +d['2018 Margin'].slice(2),\n '2016 Margin':\n d['2016 Margin'][0] === \"R\"\n ? +-d['2016 Margin'].slice(2)\n : +d['2016 Margin'].slice(2),\n '2014 Margin':\n d['2014 Margin'][0] === \"R\"\n ? +-d['2014 Margin'].slice(2)\n : +d['2014 Margin'].slice(2)\n })\n )","pinned":false,"hidden":false,"mode":"ojs"},{"id":163,"value":"appendix = md`

\n## Appendix`","pinned":false,"hidden":false,"mode":"ojs"},{"id":809,"value":"import { spark } from \"@elibenton/sparklines\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":786,"value":"function sparklineArray(values, width = 80, height = 22) {\n const x = d3\n .scaleLinear()\n .domain([0, values.length - 1])\n .range([0.5, width - 0.5]);\n const y = d3\n .scaleLinear()\n .domain(d3.extent(values))\n .range([height - 0.5, 0.5]);\n const context = DOM.context2d(width, height);\n const line = d3\n .line()\n .x((d, i) => x(i))\n .y(y)\n .context(context);\n context.beginPath(), line(values), context.stroke();\n return context.canvas;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":330,"value":"request = encodeURI(\n `https://www.googleapis.com/civicinfo/v2/representatives?key=AIzaSyAeBXmh-VC60AmBRrlc5OQBJmKQg7upwDo&address=${address}`\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":334,"value":"response = d3.json(request)","pinned":false,"hidden":false,"mode":"ojs"},{"id":359,"value":"categorizedData = d3.group(processedData, d => categorize(d.level))","pinned":false,"hidden":false,"mode":"ojs"},{"id":351,"value":"processedData = Array.from(\n d3.groups(response.offices, d => d.name),\n ([office, value]) => ({\n office,\n level: value[0].levels[0],\n politicians: value[0].officialIndices.map(d => response.officials[d])\n })\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":401,"value":"states = new Map(\n d3\n .csvParse(await FileAttachment(\"Sheet 1-States.csv\").text())\n .map(d => [d.Name, d.Abbreviation])\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":684,"value":"statesRev = new Map(\n d3\n .csvParse(await FileAttachment(\"Sheet 1-States.csv\").text())\n .map(d => [d.Abbreviation, d.Name])\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":348,"value":"function categorize(data) {\n if (data === \"country\") {\n return \"Federal\";\n } else if (data === \"administrativeArea1\") {\n return \"State\";\n } else {\n return \"Local\";\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":344,"value":"function partyColor(data) {\n if (data === \"R\") {\n return html`(R)`;\n } else if (data === \"D\") {\n return html`(D)`;\n } else {\n return html`(I)`;\n }\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":751,"value":"function color(data) {\n if (\n data.get(statesRev.get(response.normalizedInput.state)).leader[0] === \"D\"\n ) {\n return `style=\"color:#fc473a\"`;\n } else {\n return `style=\"color:#118efc\"`;\n }\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":127,"value":"function weight(cookRating) {\n if (cookRating.includes('Solid')) {\n return solid;\n } else if (cookRating.includes('Likely')) {\n return likely;\n } else if (cookRating.includes('Lean')) {\n return lean;\n } else if (cookRating.includes('Toss Up')) {\n return tossup;\n } else {\n return \"ERROR\";\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":287,"value":"import { table } from \"@tmcw/tables@513\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":52,"value":"import { slider, number, text } from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":55,"value":"import { inputsGroup } from \"@bumbeishvili/input-groups\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":628,"value":"d3 = require(\"d3@5\", \"d3-array@2\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}