32:T5c8,{ // create an object that has the candidate's names as keys and values of zero const results = all_candidates.reduce((agg, cur) => { agg[cur] = 0; return agg }, {}) // add up all of the results from every precinct data.features.forEach(d => { all_candidates.forEach(cand => { results[cand] += d.properties["results_" + subset_to_plot.value][cand] }) }) // format the data as a list of objects for Plot const to_plot = all_candidates.map(cand => ({candidate: cand, votes: results[cand]})) // add up how many ballots were cast const total_ballots = data.features.reduce((agg, cur) => agg + cur.properties["info_" + subset_to_plot.value]["BALLOTS CAST"], 0) // add up the total number of votes const total_votes = to_plot.reduce((agg, cur) => agg + cur.votes, 0) // add an item that is the difference between the ballots and votes to_plot.push({candidate: "Other / No Vote", votes: total_ballots - total_votes}) return Plot.plot({ y: { domain: d3.sort(to_plot, d => -d.votes).map(d => d.candidate) }, marginLeft: 200, marginRight: 75, marks: [ Plot.barX(to_plot, {x: "votes", y: "candidate", fill: d => d.candidate == "Other / No Vote" ? "#ccc" : d3.schemeSet2[2]}), Plot.text(to_plot, { x: "votes", y: "candidate", text: d => `${d.votes.toLocaleString()} (${Math.round(d.votes / total_ballots * 100)}%)`, textAnchor:"start" }) ] }) }33:T473,{ const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "width: 100%; height: auto; height: intrinsic;"); // we have to get at the data a couple times, so let's do that work once const accessor = d => d.properties["results_" + subset_to_plot.value][single_cand] // define a color scale const color = d3.scaleSequential(d3.interpolateYlOrRd).domain(d3.extent(data.features, accessor)) const legend = Legend(color, {tickFormat: d => d, title: "Votes per precinct"}) let val = "" svg.append("g") .selectAll("path") .data(data.features) .join("path") .attr("fill", d => { return color(accessor(d)) }) .attr("stroke", "#ccc") .attr("stroke-width", 0.25) .attr("d", path) .on("mouseover", function(e, d) { const tt = d3.select(this.parentNode.parentNode.parentNode).select(".tooltip") let val = accessor(d) tt.html(`Precinct ${d.properties.Label}
${val} votes`) }) return html` ${legend} ${svg.node()} ` }34:T4ae,{ const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "width: 100%; height: auto; height: intrinsic;"); const sorted_results = d => Object.entries(d.properties["results_" + subset_to_plot.value]).sort((a,b) => d3.descending(a[1], b[1])) const winner_obj = d => sorted_results(d)[0] const runnerup_obj = d => sorted_results(d)[1] const winner = d => winner_obj(d)[0] // define a color scale const color = candidate_ordinal svg.append("g") .selectAll("path") .data(data.features) .join("path") .attr("fill", d => { let obj = winner_obj(d) return obj[1] > 0 ? color(candidate_conversion(obj[0])) : "white" }) .attr("stroke", "#ccc") .attr("stroke-width", 0.25) .attr("d", path) .on("mouseover", function(e, d) { const tt = d3.select(this.parentNode.parentNode.parentNode).select(".tooltip") let results_markup = sorted_results(d).map(r => r.join(": ")).join("
") tt.html(`Precinct ${d.properties.Label}
${results_markup}`) }) return html` ${svg.node()} ` }35:T5d6,{ if(candidates_in_race.length < 3) { return md`_Sorry, this map is only useful in races with more than two candidates_` } const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "width: 100%; height: auto; height: intrinsic;"); const sorted_results = d => Object.entries(d.properties["results_" + subset_to_plot.value]).sort((a,b) => d3.descending(a[1], b[1])) const ballots_cast = d => d.properties["info_" + subset_to_plot.value]["BALLOTS CAST"] const winner_pct = d => sorted_results(d)[0][1] / ballots_cast(d) * 100 // define a color scale const color = anonymous_vote_share_continuous svg.append("g") .selectAll("path") .data(data.features) .join("path") .attr("fill", d => { return ballots_cast(d) == 0 ? "white" : color(winner_pct(d)) }) .attr("stroke", "#ccc") .attr("stroke-width", 0.25) .attr("d", path) .on("mouseover", function(e, d) { const tt = d3.select(this.parentNode.parentNode.parentNode).select(".tooltip") let precinct_ballots = ballots_cast(d) let results_markup = sorted_results(d).map(([cand, val]) => [cand, precinct_ballots == 0 ? 0 : Math.round(val / precinct_ballots * 100)]).map(r => r.join(": ") + "%").join("
") tt.html(`Precinct ${d.properties.Label}
${results_markup}`) }) return html` ${svg.node()} ` }36:T66d,{ if(candidates_in_race.length < 3) { return md`_Sorry, this map is only useful in races with more than two candidates_` } const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "width: 100%; height: auto; height: intrinsic;"); const sorted_results = d => Object.entries(d.properties["results_" + subset_to_plot.value]).sort((a,b) => d3.descending(a[1], b[1])) const ballots_cast = d => d.properties["info_" + subset_to_plot.value]["BALLOTS CAST"] const winner_obj = d => sorted_results(d)[0] const runnerup_obj = d => sorted_results(d)[1] const thirdp_obj = d => sorted_results(d)[2] const runner_up = d => runnerup_obj(d)[0] // define a color scale const color = candidate_ordinal svg.append("g") .selectAll("path") .data(data.features) .join("path") .attr("fill", d => { let obj = runnerup_obj(d) return obj[1] > 0 ? color(candidate_conversion(obj[0])) : "white" }) .attr("stroke", "#ccc") .attr("stroke-width", 0.25) .attr("d", path) .on("mouseover", function(e, d) { const tt = d3.select(this.parentNode.parentNode.parentNode).select(".tooltip") let precinct_ballots = ballots_cast(d) let results_markup = sorted_results(d).slice(1).map(([cand, val]) => [cand, precinct_ballots == 0 ? 0 : Math.round(val / precinct_ballots * 100)]).map(r => r.join(": ") + "%").join("
") tt.html(`Precinct ${d.properties.Label}
${results_markup}`) }) return html` ${svg.node()} ` }37:T61b,{ const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "width: 100%; height: auto; height: intrinsic;"); const accessor = (d, cand) => d.properties["results_" + subset_to_plot.value][cand] / d.properties["info_" + subset_to_plot.value]["BALLOTS CAST"] * 100 const sorted_results = d => Object.entries(d.properties["results_" + subset_to_plot.value]).sort((a,b) => d3.descending(a[1], b[1])) const ballots_cast = d => d.properties["info_" + subset_to_plot.value]["BALLOTS CAST"] const ratio = d => accessor(d, h2h_1) - accessor(d, h2h_2) // define a color scale const color = head_to_head_sequential const chosen_cands = [h2h_1, h2h_2] svg.append("g") .selectAll("path") .data(data.features) .join("path") .attr("fill", d => { return color(ratio(d)) }) .attr("stroke", "#ccc") .attr("d", path) .on("mouseover", function(e, d) { const tt = d3.select(this.parentNode.parentNode.parentNode).select(".tooltip") let precinct_ballots = ballots_cast(d) let results_markup = sorted_results(d).filter(([cand, value]) => chosen_cands.includes(cand)).map(([cand, val]) => [cand, precinct_ballots == 0 ? 0 : Math.round(val / precinct_ballots * 100)]).map(r => r.join(": ") + "%").join("
") tt.html(`Precinct ${d.properties.Label}
${results_markup}`) }) // return Legend(color) return html` ${svg.node()} ` }38:T5bf,{ const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "width: 100%; height: auto; height: intrinsic;"); // we have to get at the data a couple times, so let's do that work once const accessor = d => { let ballots = d.properties["info_" + subset_to_plot.value]["BALLOTS CAST"] let votes = Object.entries(d.properties["results_" + subset_to_plot.value]).reduce((agg, cur) => agg + cur[1], 0) return (ballots - votes) / ballots } // define a color scale const color = d3.scaleSequential(d3.interpolateReds).domain([0, race.label == "Mayor" ? 0.1 : .3]) const legend = Legend(color, {tickFormat: d => d * 100 + "%", title: "Portion of Other/Blank Votes"}) let val = "" svg.append("g") .selectAll("path") .data(data.features) .join("path") .attr("fill", d => { let val = accessor(d) return val ? color(val) : "white" }) .attr("stroke", "#ccc") .attr("stroke-width", "0.25px") .attr("d", path) .on("mouseover", function(e, d) { const tt = d3.select(this.parentNode.parentNode.parentNode).select(".tooltip") let val = accessor(d) let result = val ? `${Math.round(val * 100)}% of ballots` : "No ballots returned" tt.html(`Precinct ${d.properties.Label}
${result}`) }) return html` ${legend} ${svg.node()} ` }39:T558,{ const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "width: 100%; height: auto; height: intrinsic;"); // we have to get at the data a couple times, so let's do that work once const accessor = d => { let ballots = d.properties["info_total"]["BALLOTS CAST"] let registration = d.properties["info_total"]["REGISTRATION"] return ballots / registration } // define a color scale const color = d3.scaleSequential(d3.interpolateGreens).domain([0, 0.60]) const legend = Legend(color, {tickFormat: d => d * 100 + "%", title: "Portion of registered voters"}) let val = "" svg.append("g") .selectAll("path") .data(data.features) .join("path") .attr("fill", d => { let val = accessor(d) return val ? color(val) : "white" }) .attr("stroke", "#ccc") .attr("stroke-width", "0.25px") .attr("d", path) .on("mouseover", function(e, d) { const tt = d3.select(this.parentNode.parentNode.parentNode).select(".tooltip") let val = accessor(d) let result = val ? `${Math.round(val * 100)}% of voters` : "No registered voters" tt.html(`Precinct ${d.properties.Label}
${result}`) }) return html` ${legend} ${svg.node()} ` }3a:Te48,race_list = [{ label: "52ND ASSEMBLY", value: FileAttachment("52ND_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8048.geojson").json() }, { label: "62ND ASSEMBLY (Unfinished term)", value: FileAttachment("62ND_ASSEMBLY_DIST-U-T_06-07-22_Voter_Nominated_by_Precinct_4269-8376.geojson").json() }, { label: "56TH ASSEMBLY", value: FileAttachment("56TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8343.geojson").json() }, { label: "65TH ASSEMBLY", value: FileAttachment("65TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8345.geojson").json() }, { label: "53RD ASSEMBLY", value: FileAttachment("53RD_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8049.geojson").json() }, { label: "66TH ASSEMBLY", value: FileAttachment("66TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8058.geojson").json() }, { label: "48TH ASSEMBLY", value: FileAttachment("48TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8044.geojson").json() }, { label: "54TH ASSEMBLY", value: FileAttachment("54TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8050.geojson").json() }, { label: "39TH ASSEMBLY", value: FileAttachment("39TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8038.geojson").json() }, { label: "67TH ASSEMBLY", value: FileAttachment("67TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8346.geojson").json() }, { label: "43RD ASSEMBLY", value: FileAttachment("43RD_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8040.geojson").json() }, { label: "61ST ASSEMBLY", value: FileAttachment("61ST_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8344.geojson").json() }, { label: "69TH ASSEMBLY", value: FileAttachment("69TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8347.geojson").json() }, { label: "57TH ASSEMBLY", value: FileAttachment("57TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8052.geojson").json() }, { label: "44TH ASSEMBLY", value: FileAttachment("44TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8041.geojson").json() }, { label: "64TH ASSEMBLY", value: FileAttachment("64TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8057.geojson").json() }, { label: "41ST ASSEMBLY", value: FileAttachment("41ST_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8039.geojson").json() }, { label: "62ND ASSEMBLY", value: FileAttachment("62ND_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8055.geojson").json() }, { label: "51ST ASSEMBLY", value: FileAttachment("51ST_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8047.geojson").json() }, { label: "55TH ASSEMBLY", value: FileAttachment("55TH_ASSEMBLY_DIST_06-07-22_Voter_Nominated_by_Precinct_4269-8051.geojson").json() }, { label: "49TH ASSEMBLY", value: 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30:{"title":"June 7, 2022 Los Angeles County election results for California Assembly","cells":[{"id":0,"value":"# June 7, 2022 Los Angeles County election results for California Assembly\n\nUse this notebook to explore the results of the 2022 LA County primary elections for assembly. I created this very quickly and have spot checked the data, but there might be some little bugs here and there.\n\nFor the underlying data and shapefiles see [this github repo](https://github.com/yanofsky/la-2022-primary-shapefiles) which includes data for all races in LA County","pinned":false,"hidden":false,"mode":"md"},{"id":303,"value":"## Pick which race you want to look at \n\nAlso you can filter which set of ballots you're interested in. \n\n_Unless otherwise noted, your choices here are applied to all of the maps._","pinned":false,"hidden":false,"mode":"md"},{"id":9,"value":"viewof race = Inputs.select(race_list.sort((a,b)=> d3.ascending(a.label,b.label)), {label: \"Choose a race\", format: x => x.label})","pinned":false,"hidden":false,"mode":"ojs"},{"id":66,"value":"viewof subset_to_plot = Inputs.select([{\n label: \"All ballots\",\n value: \"total\"\n},\n{\n label: \"Vote by mail only\",\n value: \"vbm\"\n},\n{\n label: \"In-person only\",\n value: \"polling_place\"\n}], {label: \"Which set of ballots do you want to look at?\", format: x => x.label})","pinned":false,"hidden":false,"mode":"ojs"},{"id":340,"value":"md`## The overall results\nThis is how each candidate did district wide for **${subset_to_plot.label}**\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":342,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":501,"value":"_\"Other/No Vote\" is the difference between the candidate totals and the number of ballots cast_","pinned":false,"hidden":false,"mode":"md"},{"id":104,"value":"## Single Candidate Results\nThis map shows the results of the selected candidate. It's helpful to see where in the district they had the most _relative_ support.","pinned":false,"hidden":false,"mode":"md"},{"id":132,"value":"viewof single_cand = Inputs.select(Object.keys(data.features[0].properties.results_total))","pinned":false,"hidden":false,"mode":"ojs"},{"id":80,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":147,"value":"## Best performing candidate in each precinct\nThis map shows each precinct colored by the candidate that got the most votes. It's helpful to see which candidate won the precinct\n\nThe circles show the size of the lead. Smaller circles indicate that the winner of the precinct didn't win by many more votes than the runner up.","pinned":false,"hidden":false,"mode":"md"},{"id":167,"value":"Swatches(candidate_ordinal.domain(candidates_in_race))","pinned":false,"hidden":false,"mode":"ojs"},{"id":152,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":310,"value":"## The most contested precincts\nThis map shows the portion of the vote won by the candidate with the most votes—no matter who it is. Precincts with lower values indicate there was more differing opinions of the voters.","pinned":false,"hidden":false,"mode":"md"},{"id":326,"value":"html`\n${Legend(anonymous_vote_share_continuous, {tickFormat: d => d + \"%\", title: \"Precinct winner's vote share\"})}\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":314,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":183,"value":"## Runner up in each precinct\nThis map shows the district with each precinct colored by the candidate that came in second. It's helpful to get a sense of which candidates voters were deciding between\n\nThe circles show the size of the lead over the third-place candidate. Smaller circles indicate that the runner-up of the precinct didn't win by many more votes than the third-place candidate.","pinned":false,"hidden":false,"mode":"md"},{"id":192,"value":"Swatches(candidate_ordinal.domain(candidates_in_race))","pinned":false,"hidden":false,"mode":"ojs"},{"id":181,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":224,"value":"## Head to head spreads\nPick two candidates to compare the percentage point difference of their vote totals from precinct to precinct. This is helpful to see where candidates won a similar share of votes or a differing share of vote.","pinned":false,"hidden":false,"mode":"md"},{"id":226,"value":"viewof h2h_1 = Inputs.select(all_candidates, {label: \"Select a candidate\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":231,"value":"viewof h2h_2 = Inputs.select(all_candidates.filter(d => d != h2h_1 && d != \"Others\"), {label: \"Select another candidate\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":273,"value":"html`\n${Legend(head_to_head_sequential, {tickFormat: d => d + \" pp\"})}\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":244,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":504,"value":"md`## Head to head plot\nAnother way to look at this same data is through a scatter plot. \n\nIf the cluster of dots slope down to the right, the candidates were successful in different precincts (i.e. negatively correlated). If the dots slope up to the right, the candidates were successful in the same precincts (i.e. positively correlated).\n\nIgnoring precincts with less than 10 ballots, the correlation of **${subset_to_plot.label}** between **${h2h_1}** and **${h2h_2}** is **${Math.round(h2h_correlation*1000)/1000}**`","pinned":false,"hidden":false,"mode":"ojs"},{"id":506,"value":"{\n if(candidates_in_race.length < 3) {\n return md`_Sorry, this chart is only useful in races with more than two candidates_`\n }\n\n return Plot.plot({\n x: {\n label: `${h2h_1} vote share →`,\n },\n\n y: {\n label: `↑ ${h2h_2} vote share`,\n },\n\n marks: [\n Plot.dot(\n data.features,\n {\n x: d => d.properties[\"results_\" + subset_to_plot.value][h2h_1] / d.properties[\"info_\" + subset_to_plot.value][\"BALLOTS CAST\"] * 100,\n y: d => d.properties[\"results_\" + subset_to_plot.value][h2h_2] / d.properties[\"info_\" + subset_to_plot.value][\"BALLOTS CAST\"] * 100,\n stroke: d3.schemeSet2[2],\n opacity: 0.25\n }\n )\n ]\n \n})\n \n}\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":539,"value":"h2h_correlation = Correlation()\n .x(d => d.properties[\"results_\" + subset_to_plot.value][h2h_1] / d.properties[\"info_\" + subset_to_plot.value][\"BALLOTS CAST\"] * 100)\n .y(d => d.properties[\"results_\" + subset_to_plot.value][h2h_2] / d.properties[\"info_\" + subset_to_plot.value][\"BALLOTS CAST\"] * 100)(data.features.filter(d => d.properties[\"info_\" + subset_to_plot.value][\"BALLOTS CAST\"] >= 10))","pinned":false,"hidden":false,"mode":"ojs"},{"id":580,"value":"## The voters who didn't vote\nNot everyone who returned a ballot voted in this race, or for a listed candidate. This is where those voters live.\n\nThis is _not_ where turnout was low. This is where voters decided not to vote in this race.","pinned":false,"hidden":false,"mode":"md"},{"id":584,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":595,"value":"## Turnout\nNot everyone who is registered to vote, decided to vote or got their ballots in on time.\n\n_This map only shows **total registration** and is not filtered to your selected subset_","pinned":false,"hidden":false,"mode":"md"},{"id":597,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":528,"value":"## The end\nThat's it for this tool. Everything below is just code that helps make everything above work!","pinned":false,"hidden":false,"mode":"md"},{"id":317,"value":"anonymous_vote_share_continuous = d3.scaleSequential(d3.interpolateMagma).domain([0, 50])","pinned":true,"hidden":false,"mode":"ojs"},{"id":269,"value":"head_to_head_sequential = d3.scaleSequential(d3.interpolateRdYlBu).domain([-50,50])","pinned":true,"hidden":false,"mode":"ojs"},{"id":175,"value":"candidate_ordinal = d3.scaleOrdinal(d3.schemeSet2).domain(candidates_in_race)","pinned":true,"hidden":false,"mode":"ojs"},{"id":20,"value":"projection = d3.geoMercator().rotate([118,0,0]).fitExtent([[0,0], [width, height]], data)","pinned":true,"hidden":false,"mode":"ojs"},{"id":22,"value":"path = d3.geoPath(projection)","pinned":true,"hidden":false,"mode":"ojs"},{"id":24,"value":"width = 1000","pinned":true,"hidden":false,"mode":"ojs"},{"id":26,"value":"height = 500","pinned":true,"hidden":false,"mode":"ojs"},{"id":155,"value":"candidates_in_race = [...Object.keys(data.features[0].properties.results_total)]","pinned":true,"hidden":false,"mode":"ojs"},{"id":645,"value":"candidate_conversion = d => candidates_in_race.includes(d) ? d : \"Others\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":622,"value":"all_candidates = Object.keys(data.features[0].properties.results_total)","pinned":true,"hidden":false,"mode":"ojs"},{"id":664,"value":"data","pinned":true,"hidden":false,"mode":"ojs"},{"id":625,"value":"all_candidate_totals = {\n // create an object that has the candidate's names as keys and values of zero\n const results = all_candidates.reduce((agg, cur) => {\n agg[cur] = 0; \n return agg\n }, {})\n\n // add up all of the results from every precinct\n data.features.forEach(d => {\n all_candidates.forEach(cand => {\n results[cand] += d.properties[\"results_\" + subset_to_plot.value][cand]\n })\n })\n\n return results\n \n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":12,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"data = await race.value","pinned":true,"hidden":false,"mode":"ojs"},{"id":572,"value":"","pinned":false,"hidden":false,"mode":"html"},{"id":75,"value":"import {Choropleth} from \"@d3/choropleth\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":99,"value":"import {Swatches} from \"@d3/color-legend\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":262,"value":"import {Legend} from \"@d3/color-legend\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":443,"value":"import { Tooltip } from \"@clhenrick/tooltip-component\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":535,"value":"import { Correlation } from \"@harrystevens/correlation\"","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W3b","stdlib":"1","titling":"auto"}