31:T2429,html`

${(() => { // Filter for Electoral College and Kamala Harris const filteredCandidates = electionData .filter(item => item.State === 'Electoral College'); const silver = silver_odds; const econ = economist_odds; return filteredCandidates.map(candidate => { const fteOdds = (candidate.FTE * 100).toFixed(0); const standardOdds = (candidate.Standard * 100).toFixed(0); const ddhqOdds = (candidate.DDHQ * 100).toFixed(0); const rwhOdds = (candidate.RWH * 100).toFixed(0); const silverOdds = (silver * 100).toFixed(0); const econOdds = (econ * 100).toFixed(0); const fteColor = harrisColorScale(candidate.FTE); const standardColor = harrisColorScale(candidate.Standard); const ddhqColor = harrisColorScale(candidate.DDHQ); const rwhColor = harrisColorScale(candidate.RWH); const silverColor = harrisColorScale(silver); const econColor = harrisColorScale(econ); return html` `; }); })()} ${(() => { // Filter for Electoral College and Kamala Harris const filteredCandidates = electionData .filter(item => item.State === 'Electoral College'); const silver = silver_odds; const econ = economist_odds return filteredCandidates.map(candidate => { const fteOdds = (99.7 - (candidate.FTE * 100)).toFixed(0); const standardOdds = (99.5 - (candidate.Standard * 100)).toFixed(0); const ddhqOdds = (100 - (candidate.DDHQ * 100)).toFixed(0); const rwhOdds = (99.5 - (candidate.RWH * 100)).toFixed(0); const silverOdds = (99.6 - (silver * 100)).toFixed(0); const econOdds = (100 - (econ * 100)).toFixed(0); const fteColor = trumpColorScale(0.997 - candidate.FTE); const standardColor = trumpColorScale(0.995 - candidate.Standard); const ddhqColor = trumpColorScale(1 - candidate.DDHQ); const rwhColor = trumpColorScale(0.995 - candidate.RWH); const silverColor = trumpColorScale(0.996 - silver); const econColor = trumpColorScale(1 - econ); return html` `; }); })()}

Candidate	538 Odds	JHK Odds	DDHQ Odds	RWH Odds	*Silver Odds	*Econ Odds
Kamala Harris	${fteOdds}%	${standardOdds}%	${ddhqOdds}%	${rwhOdds}%	${silverOdds}%	${econOdds}%
Donald Trump	${fteOdds}%	${standardOdds}%	${ddhqOdds}%	${rwhOdds}%	${silverOdds}%	${econOdds}%

*Silver Bulletin odds from tweet on 11/4, state odds for Silver Bulletin and The Economist are behind a paywall.

` 32:T18cd,state_barchart = { // Set height based on the selected model option const height = models === 'Model Avg.' ? 150 : 300; // Filter state_stacked_data based on selected model option const filtered_data = models === 'Model Avg.' ? state_stacked_data.filter(d => d.model === 'Model Avg.') // || d.model === 'JHK' : state_stacked_data.filter(d => d.model != 'Model Avg.'); const svg = d3.create("svg") .attr("viewBox", [0, 0, width, height]) .attr("width", width) .attr("height", height); // Define scales based on competitive view const xDomain = competitive === 'Competitive' ? [215, 325] : [0, 538]; const x = d3.scaleLinear() .domain(xDomain) .range([0, width - 95]); const y = d3.scaleBand() .domain(filtered_data.map(d => d.model)) .range([40, height - 40]) .padding(0.1); // Define axes based on competitive view const xAxis = d3.axisBottom(x) .ticks(competitive === 'Competitive' ? 10 : 10) .tickSize(6) .tickSizeOuter(0) .tickFormat(d => d % 50 === 0 ? d : d); let tooltipOpen = false; function clearTooltip() { tooltipOpen = false; svg.selectAll("rect").style("stroke", "none"); tooltip.style("visibility", "hidden") .style("pointer-events", "none"); } // Add "270 votes to win" label svg.append("text") .attr("x", x(269) + 70) .attr("y", 20) .attr("text-anchor", "middle") .attr("font-size", "14px") .attr("font-family", "helvetica") .attr("font-weight", "bold") .attr("fill", "black") .text("270 votes to win"); const modelGroups = svg.selectAll(".model-group") .data(filtered_data) .join("g") .attr("class", "model-group") .attr("transform", d => `translate(70, ${y(d.model)})`); // Append bars for each state modelGroups.selectAll(".bar") .data(d => d.data) .join("rect") .attr("x", d => competitive === 'Competitive' ? Math.max(x(d.cumulativeVotes - d.electoralVotes), x(215)) : x(d.cumulativeVotes - d.electoralVotes)) .attr("y", 0) .attr("width", d => competitive === 'Competitive' ? Math.max(0, x(d.cumulativeVotes) - Math.max(x(d.cumulativeVotes - d.electoralVotes), x(215))) : Math.max(0, x(d.cumulativeVotes) - x(d.cumulativeVotes - d.electoralVotes))) .attr("height", y.bandwidth()) .attr("fill", d => electionColorScale(d.value)) .on("mouseover", function(event, d) { if (!tooltipOpen) { d3.select(this).style("stroke", "black").style("stroke-width", "1px"); tooltip.style("visibility", "visible") .html(`${d.name} - ${d.electoralVotes} Electoral Votes
Harris Odds: ${Math.round(d.value * 100)}%`); } }) .on("mousemove", function(event) { if (!tooltipOpen) { const tooltipWidth = tooltip.node().offsetWidth; const tooltipHeight = tooltip.node().offsetHeight; const pageX = event.pageX; const pageY = event.pageY; const xPosition = pageX + tooltipWidth + 20 > window.innerWidth ? pageX - tooltipWidth - 10 : pageX + 10; const yPosition = pageY + tooltipHeight + 20 > window.innerHeight ? pageY - tooltipHeight - 10 : pageY + 10; tooltip.style("top", yPosition + "px") .style("left", xPosition + "px"); } }) .on("mouseout", function() { if (!tooltipOpen) { d3.select(this).style("stroke", "none"); tooltip.style("visibility", "hidden"); } }) .on("click", function(event, d) { if (tooltipOpen) { clearTooltip(); } else { clearTooltip(); tooltipOpen = true; d3.select(this).style("stroke", "black").style("stroke-width", "1px"); tooltip.style("visibility", "visible") .html(`${d.name} - ${d.electoralVotes} Electoral Votes
Harris Odds: ${Math.round(d.value * 100)}%`) .style("top", event.pageY + "px") .style("left", event.pageX + "px") .style("pointer-events", "auto"); } }); modelGroups.selectAll(".label") .data(d => d.data) .join("text") .attr("x", d => { const barStart = x(d.cumulativeVotes - d.electoralVotes); const barWidth = x(d.cumulativeVotes) - barStart; const textWidth = 10; return barWidth > textWidth ? barStart + barWidth / 2 : -10; }) .attr("y", y.bandwidth() / 2) .attr("dy", "-0.35em") .attr("text-anchor", "middle") .attr("fill", "black") .attr("font-size", "8px") .attr("font-family", "Arial") .style("display", d => { const barWidth = x(d.cumulativeVotes) - x(d.cumulativeVotes - d.electoralVotes); return barWidth > 10 ? null : "none"; }) .each(function(d) { const stateName = d.name; const textElement = d3.select(this); stateName.split("").forEach((letter, i) => { textElement.append("tspan") .attr("x", textElement.attr("x")) .attr("dy", i === 0 ? "0em" : "1em") .text(letter); }); }); modelGroups.append("text") .attr("x", width - 92) .attr("y", y.bandwidth() / 2) .attr("dy", ".35em") .attr("text-anchor", "start") .attr("fill", "#0b70db") .attr("font-weight", "bold") .attr("font-size", "12px") .attr("font-family", "Arial") .text(d => { const harrisElectoralVotes = d.data .filter(s => s.value >= 0.5) .reduce((sum, s) => sum + s.electoralVotes, 0); return competitive === 'Competitive' ? "" : ` ${harrisElectoralVotes}`; }); svg.append("g") .attr("class", "x-axis") .attr("transform", `translate(70,${height - 40})`) .call(xAxis); svg.append("g") .attr("class", "y-axis") .attr("transform", `translate(70, 0)`) .call(d3.axisLeft(y).ticks(10).tickSize(0)) .selectAll("text") .attr("font-weight", "bold") .attr("font-size", "11px"); svg.append("line") .attr("x1", x(269) + 70) .attr("x2", x(269) + 70) .attr("y1", 30) .attr("y2", height - 40) .attr("stroke", "black") .attr("stroke-width", 1) .attr("stroke-dasharray", "4 2"); return svg.node(); } 33:T738,html` ${models_table === 'All Models' ? html` ${electionData .filter(d => competitive_table === 'All States' || isCompetitive(d)) .map(d => html` `)}

State	538	JHK	DDHQ	RWH
${d.State}	${(d.FTE * 100).toFixed(0)}%	${(d.Standard * 100).toFixed(0)}%	${(d.DDHQ * 100).toFixed(0)}%	${(d.RWH * 100).toFixed(0)}%

` : html` ${electionData .filter(d => competitive_table === 'All States' || isCompetitive(d)) .map(d => html` `)}

State	Model Avg.
${d.State}	${(d.ModelAvg * 100).toFixed(0)}%

`}
`34:T129f,plot = { const xAxisLabel = { '538': '538 Harris Odds', 'DDHQ': 'DDHQ Harris Odds', 'JHK': 'JHK Harris Odds', 'RWH': 'RWH Harris Odds', 'Model Avg.': 'Model Avg. Harris Odds' }; const yAxisLabel = { '538': '538 Harris Odds', 'DDHQ': 'DDHQ Harris Odds', 'JHK': 'JHK Harris Odds', 'RWH': 'RWH Harris Odds', 'Model Avg.': 'Model Avg. Harris Odds' }; const xValue = d => { switch (x_axis) { case '538': return d.FTE; case 'DDHQ': return d.DDHQ; case 'JHK': return d.Standard; case 'RWH': return d.RWH; case 'Model Avg.': return d.ModelAvg; default: return d.FTE; } }; const yValue = d => { switch (y_axis) { case '538': return d.FTE; case 'DDHQ': return d.DDHQ; case 'JHK': return d.Standard; case 'RWH': return d.RWH; case 'Model Avg.': return d.ModelAvg; default: return d.DDHQ; } }; const annotationText = { '538': { '538': '538 Favors Harris', 'DDHQ': 'DDHQ Favors Harris', 'JHK': 'JHK Favors Harris', 'RWH': 'RWH Favors Harris', 'Model Avg.': 'Model Avg. Favors Harris' }, 'DDHQ': { '538': '538 Favors Harris', 'DDHQ': 'DDHQ Favors Harris', 'JHK': 'JHK Favors Harris', 'RWH': 'RWH Favors Harris', 'Model Avg.': 'Model Avg. Favors Harris' }, 'JHK': { '538': '538 Favors Harris', 'DDHQ': 'DDHQ Favors Harris', 'JHK': 'JHK Favors Harris', 'RWH': 'RWH Favors Harris', 'Model Avg.': 'Model Avg. Favors Harris' }, 'RWH': { '538': '538 Favors Harris', 'DDHQ': 'DDHQ Favors Harris', 'JHK': 'JHK Favors Harris', 'RWH': 'RWH Favors Harris', 'Model Avg.': 'Model Avg. Favors Harris' }, 'Model Avg.': { '538': '538 Favors Harris', 'DDHQ': 'DDHQ Favors Harris', 'JHK': 'JHK Favors Harris', 'RWH': 'RWH Favors Harris', 'Model Avg.': 'Model Avg. Favors Harris' } }; const favoredTextX = annotationText[x_axis][y_axis]; const favoredTextY = annotationText[y_axis][x_axis]; return Plot.plot({ x: { label: xAxisLabel[x_axis], domain: [0, 1], tickFormat: d => `${(d * 100).toFixed(0)}%`, tickSize: 0, tickPadding: 8, labelOffset: 40, }, y: { label: yAxisLabel[y_axis], domain: [0, 1], tickFormat: d => `${(d * 100).toFixed(0)}%`, tickSize: 0, tickPadding: 8, labelOffset: 80, labelRotate: -90, }, marginLeft: 80, marginBottom: 80, height: 500, width: 650, color: { legend: false, }, grid: true, marks: [ Plot.dot( mergedData.filter(d => d.Abbreviation !== ""), { x: xValue, y: yValue, r: 15, fill: d => electionColorScale(xValue(d)), stroke: "black", strokeWidth: 1, opacity: 0.7, title: d => `${d.Abbreviation}: Electoral Votes ${d.electoralVotes}, ${x_axis} ${Math.round(xValue(d) * 100)}%, ${y_axis} ${Math.round(yValue(d) * 100)}%`, } ), Plot.dot( mergedData.filter(d => d.Abbreviation === ""), { x: xValue, y: yValue, r: 5, fill: d => electionColorScale(xValue(d)), stroke: "black", strokeWidth: 1, symbol: "star", // Ensure "star" symbol is used for Electoral College title: d => `${d.Abbreviation}: Electoral Votes ${d.electoralVotes}, ${x_axis} ${Math.round(xValue(d) * 100)}%, ${y_axis} ${Math.round(yValue(d) * 100)}%`, } ), Plot.line( [{x: 0, y: 0}, {x: 1, y: 1}], { x: "x", y: "y", stroke: "black", strokeWidth: 2, strokeDasharray: "4 2", } ), Plot.text( mergedData.filter(d => d.Abbreviation !== ""), { x: xValue, y: yValue, text: d => d.Abbreviation, dy: 0, fontSize: 10, fill: "black", textAnchor: "middle", } ), // Annotations with text and arrows Plot.text( [{x: 0.3, y: 0.7, text: favoredTextX}, {x: 0.7, y: 0.3, text: favoredTextY}], { x: d => d.x, y: d => d.y, text: d => d.text, fontSize: 14, fontWeight: "bold", fill: "black", fontFamily: "Helvetica", textAnchor: "middle", dy: -15, dx: 10, } ) ], style: { fontFamily: "Helvetica Neue, Helvetica, serif", fontSize: "16px", } }); } 35:Tbd9,html`

${modelsData.map(model => { const expCorrectCalls = model.ExpcorrectCalls.toFixed(1); const correctCalls = model.correctCalls.toFixed(1); const exppercentCorrect = ((model.ExpcorrectCalls / model.totalCalls) * 100).toFixed(1); const correctPercent = (model.correctPercent * 100).toFixed(1); // Define a color based on the percentCorrect value let backgroundColor; if (correctPercent < 90) { // Light green for lower values backgroundColor = `rgba(144, 238, 144, ${(correctPercent - 90) / (93 - 90)})`; // From light green to darker green } else { // Darker green for higher values backgroundColor = `rgba(34, 139, 34, ${(correctPercent - 91) / (100 - 90)})`; // From dark green to a deeper shade } return html` `; })}

Model	# of Contests	# Exp. Correct Calls	# Correct Calls	% Exp. Correct Calls	% Correct Calls
${model.name}	${model.totalCalls}	${expCorrectCalls}	${correctCalls}	${exppercentCorrect}%	${correctPercent}%

`; 36:T534,modelsData = [ { name: "FiveThirtyEight", ExpcorrectCalls: d3.sum(electionData, d => (d.State !== "Electoral College" ? (d.FTE < 0.5 ? 1 - d.FTE : d.FTE) : 0)), totalCalls: d3.sum(electionData, d => d.State !== "Electoral College" ? 1 : 0), correctCalls: 52, correctPercent: 0.92857 }, { name: "JHK", ExpcorrectCalls: d3.sum(electionData, d => (d.State !== "Electoral College" ? (d.Standard < 0.5 ? 1 - d.Standard : d.Standard) : 0)), totalCalls: d3.sum(electionData, d => d.State !== "Electoral College" ? 1 : 0), correctCalls: 54, correctPercent: 0.96428 }, { name: "Race to WH", ExpcorrectCalls: d3.sum(electionData, d => (d.State !== "Electoral College" ? (d.RWH < 0.5 ? 1 - d.RWH : d.RWH) : 0)), totalCalls: d3.sum(electionData, d => d.State !== "Electoral College" ? 1 : 0), correctCalls: 52, correctPercent: 0.92857 }, { name: "Decision Desk", ExpcorrectCalls: d3.sum(electionData, d => (d.State !== "Electoral College" ? (d.DDHQ < 0.5 ? 1 - d.DDHQ : d.DDHQ) : 0)), totalCalls: d3.sum(electionData, d => d.State !== "Electoral College" ? 1 : 0), correctCalls: 55, correctPercent: 0.98214 }, { name: "Silver Bulletin", ExpcorrectCalls: 51.5, totalCalls: 56, correctCalls: 54, correctPercent: 0.96428 } ]; 37:T1434,function make_tilegram() { let div = d3 .create('div') .style("width", width) .style("height", `${height}px`) .style('overflow', 'hidden'); let svg = div .append('svg') .style('overflow', 'hidden') .attr("viewBox", [0, 0, width, height]); let map_obj, hex_data, boundary_data; if (map_type == 'Together') { map_obj = tiles; hex_data = tiles; boundary_data = tile_boundaries; } else if (map_type == 'Broken') { map_obj = broken_tiles; hex_data = broken_tiles; boundary_data = broken_tile_boundaries; } let proj = d3 .geoIdentity() .reflectY(true) .fitSize([width, height], map_obj); let path = d3.geoPath().projection(proj); let map = svg.append('g'); map .selectAll("path.tile") .data(hex_data.features) .join("path") .attr('class', 'tile') .attr('d', path) .style("fill", function(d) { let fips = d.id; let info = info_map.get(fips); let p; if (shade_by == "538") { p = info.FTE; return d3.scaleLinear([0, 0.5, 1], ["#ea5353", "#fafafa", "#3487e0"])(p); } else if (shade_by == "JHK") { p = info.Standard; return d3.scaleLinear([0, 0.5, 1], ["#ea5353", "#fafafa", "#3487e0"])(p); } else if (shade_by == "DDHQ") { p = info.DDHQ; return d3.scaleLinear([0, 0.5, 1], ["#ea5353", "#fafafa", "#3487e0"])(p); } else if (shade_by == "RWH") { p = info.RWH; return d3.scaleLinear([0, 0.5, 1], ["#ea5353", "#fafafa", "#3487e0"])(p); } }) .attr('data-state', d => d.id) .attr("stroke-width", '0.5px') .attr("stroke", "white") .attr("stroke-linejoin", "round"); // Add state abbreviation text above each hexagon map .selectAll("text.abbr.black") .data(hex_data.features) .join("text") .attr("class", "abbr") .attr("x", d => path.centroid(d)[0]) .attr("y", d => path.centroid(d)[1]) .attr("text-anchor", "middle") .attr("font-size", () => { // Dynamically set font size based on screen width let screenWidth = window.innerWidth; let fontSize = d3.scaleLinear() .domain([300, 1000]) .range([5, 10]) .clamp(true); return `${fontSize(screenWidth)}px`; }) .attr("font-family", "helvetica") .attr("font-weight", "bold") .attr("stroke", "black") .attr("stroke-width", 1) .attr("stroke-linejoin", "round") .attr("fill", "black") .text(d => { let fips = d.id; let info = info_map.get(fips); return info ? info.abbr : ''; }); // Add state abbreviation text above each hexagon map .selectAll("text.abbr.white") .data(hex_data.features) .join("text") .attr("class", "abbr") .attr("x", d => path.centroid(d)[0]) .attr("y", d => path.centroid(d)[1]) .attr("text-anchor", "middle") .attr("font-size", () => { // Dynamically set font size based on screen width let screenWidth = window.innerWidth; let fontSize = d3.scaleLinear() .domain([300, 1000]) .range([5, 10]) .clamp(true); return `${fontSize(screenWidth)}px`; }) .attr("font-family", "helvetica") .attr("font-weight", "bold") .attr("stroke-linejoin", "round") .attr("fill", "white") .text(d => { let fips = d.id; let info = info_map.get(fips); return info ? info.abbr : ''; }); map .selectAll("path.boundary") .data(boundary_data.features) .join("path") .attr('class', 'boundary') .attr('d', path) .style('fill', 'black') .style("fill-opacity", 0) .attr("stroke-width", '1px') .attr("stroke", "black") .attr("stroke-linejoin", "round") .attr('data-state', d => d.id) .on('pointerenter mouseenter', function(evt) { let copy = this.cloneNode(true); copy.setAttribute('stroke', 'black'); copy.setAttribute('stroke-width', '6px'); copy.setAttribute('class', 'temp'); copy.addEventListener('mouseleave', function() { map.selectAll('.temp').remove(); }); let fips = d3.select(evt.target).attr('data-state'); let info = info_map.get(fips); // Format FTE and Standard as percentages and round them let FTE_percentage = Math.round(info.FTE * 100) + '%'; let Standard_percentage = Math.round(info.Standard * 100) + '%'; let DDHQ_percentage = Math.round(info.DDHQ * 100) + '%'; let RWH_percentage = Math.round(info.RWH * 100) + '%'; tippy(copy, { allowHTML: true, duration: 100, maxWidth: 420, theme: 'light', content: `

State	Votes	538	JHK	DDHQ	RWH
${info.name}	${info.electoralVotes}	${FTE_percentage}	${Standard_percentage}	${DDHQ_percentage}	${RWH_percentage}

` }); map.append(() => copy); }); return div.node(); } 38:T808,electoralVotes = [ { state: "Alabama", votes: 9 }, { state: "Alaska", votes: 3 }, { state: "Arizona", votes: 11 }, { state: "Arkansas", votes: 6 }, { state: "California", votes: 54 }, { state: "Colorado", votes: 10 }, { state: "Connecticut", votes: 7 }, { state: "Delaware", votes: 3 }, { state: "District Of Columbia", votes: 3 }, { state: "Florida", votes: 30 }, { state: "Georgia", votes: 16 }, { state: "Hawaii", votes: 4 }, { state: "Idaho", votes: 4 }, { state: "Illinois", votes: 19 }, { state: "Indiana", votes: 11 }, { state: "Iowa", votes: 6 }, { state: "Kansas", votes: 6 }, { state: "Kentucky", votes: 8 }, { state: "Louisiana", votes: 8 }, { state: "Maine", votes: 2 }, { state: "Maine Cd 1", votes: 1 }, { state: "Maine Cd 2", votes: 1 }, { state: "Maryland", votes: 10 }, { state: "Massachusetts", votes: 11 }, { state: "Michigan", votes: 15 }, { state: "Minnesota", votes: 10 }, { state: "Mississippi", votes: 6 }, { state: "Missouri", votes: 10 }, { state: "Montana", votes: 4 }, { state: "Nebraska", votes: 2 }, { state: "Nebraska Cd 1", votes: 1 }, { state: "Nebraska Cd 2", votes: 1 }, { state: "Nebraska Cd 3", votes: 1 }, { state: "Nevada", votes: 6 }, { state: "New Hampshire", votes: 4 }, { state: "New Jersey", votes: 14 }, { state: "New Mexico", votes: 5 }, { state: "New York", votes: 28 }, { state: "North Carolina", votes: 16 }, { state: "North Dakota", votes: 3 }, { state: "Ohio", votes: 17 }, { state: "Oklahoma", votes: 7 }, { state: "Oregon", votes: 8 }, { state: "Pennsylvania", votes: 19 }, { state: "Rhode Island", votes: 4 }, { state: "South Carolina", votes: 9 }, { state: "South Dakota", votes: 3 }, { state: "Tennessee", votes: 11 }, { state: "Texas", votes: 40 }, { state: "Utah", votes: 6 }, { state: "Vermont", votes: 3 }, { state: "Virginia", votes: 13 }, { state: "Washington", votes: 12 }, { state: "West Virginia", votes: 4 }, { state: "Wisconsin", votes: 10 }, { state: "Wyoming", votes: 3 } ]; 39:T652,stacked_data = { const bucketOrder = [ "0-10%", "10-20%", "20-30%", "30-40%", "40-50%", "50-60%", "60-70%", "70-80%", "80-90%", "90-100%" ]; // Flatten the merged data const flatData = mergedData.flatMap(d => [ {name: d.State, model: "538", value: d.FTE, electoralVotes: d.electoralVotes}, {name: d.State, model: "JHK", value: d.Standard, electoralVotes: d.electoralVotes}, {name: d.State, model: "DDHQ", value: d.DDHQ, electoralVotes: d.electoralVotes}, {name: d.State, model: "RWH", value: d.RWH, electoralVotes: d.electoralVotes}, {name: d.State, model: "Model Avg.", value: d.ModelAvg, electoralVotes: d.electoralVotes}, ]); // Group by model and bucket, summing up the electoral votes const groupedData = d3.rollups( flatData, v => d3.sum(v, d => d.electoralVotes), d => d.model, d => { const value = d.value; if (value <= 0.1) return "0-10%"; if (value <= 0.2) return "10-20%"; if (value <= 0.3) return "20-30%"; if (value <= 0.4) return "30-40%"; if (value <= 0.5) return "40-50%"; if (value <= 0.6) return "50-60%"; if (value <= 0.7) return "60-70%"; if (value <= 0.8) return "70-80%"; if (value <= 0.9) return "80-90%"; return "90-100%"; } ); // Convert the grouped data back to an array format suitable for D3 stacking const stackedData = Array.from(groupedData, ([model, buckets]) => { const obj = {model}; // Sort the buckets by the predefined order bucketOrder.forEach(bucket => { obj[bucket] = buckets.find(([b, _]) => b === bucket)?.[1] || 0; }); return obj; }); return stackedData; // Output the processed data }3a:Ta6c,state_stacked_data = { // Table of state abbreviations const stateAbbreviations = { "Alabama": "AL", "Alaska": "AK", "Arizona": "AZ", "Arkansas": "AR", "California": "CA", "Colorado": "CO", "Connecticut": "CT", "District Of Columbia":"DC", "Delaware": "DE", "Florida": "FL", "Georgia": "GA", "Hawaii": "HI", "Idaho": "ID", "Illinois": "IL", "Indiana": "IN", "Iowa": "IA", "Kansas": "KS", "Kentucky": "KY", "Louisiana": "LA", "Maine": "ME", "Maryland": "MD", "Massachusetts": "MA", "Michigan": "MI", "Minnesota": "MN", "Mississippi": "MS", "Missouri": "MO", "Montana": "MT", "Nebraska": "NE", "Nevada": "NV", "New Hampshire": "NH", "New Jersey": "NJ", "New Mexico": "NM", "New York": "NY", "North Carolina": "NC", "North Dakota": "ND", "Ohio": "OH", "Oklahoma": "OK", "Oregon": "OR", "Pennsylvania": "PA", "Rhode Island": "RI", "South Carolina": "SC", "South Dakota": "SD", "Tennessee": "TN", "Texas": "TX", "Utah": "UT", "Vermont": "VT", "Virginia": "VA", "Washington": "WA", "West Virginia": "WV", "Wisconsin": "WI", "Wyoming": "WY", // For Maine CD 2 and other specific districts "Maine Cd 1": "ME-1", "Maine Cd 2": "ME-2", "Nebraska Cd 1": "NE-1", "Nebraska Cd 2": "NE-2", "Nebraska Cd 3": "NE-3" }; // Filter out entries with "Electoral College" const filteredData = mergedData.filter(d => d.State !== "Electoral College"); // Flatten the filtered data const flatData = filteredData.flatMap(d => [ {name: stateAbbreviations[d.State] || d.State, model: "538", value: d.FTE, electoralVotes: d.electoralVotes}, {name: stateAbbreviations[d.State] || d.State, model: "JHK", value: d.Standard, electoralVotes: d.electoralVotes}, {name: stateAbbreviations[d.State] || d.State, model: "DDHQ", value: d.DDHQ, electoralVotes: d.electoralVotes}, {name: stateAbbreviations[d.State] || d.State, model: "RWH", value: d.RWH, electoralVotes: d.electoralVotes}, {name: stateAbbreviations[d.State] || d.State, model: "Model Avg.", value: d.ModelAvg, electoralVotes: d.electoralVotes}, ]); // Group by model and sort states by probability const groupedData = d3.group( flatData, d => d.model ); // Convert the grouped data into a format suitable for stacked bar charts const stackedData = []; groupedData.forEach((states, model) => { // Sort states by value and calculate cumulative electoral votes const sortedStates = states.sort((a, b) => a.value - b.value); let cumulativeVotes = 0; const cumulativeData = sortedStates.map(state => { cumulativeVotes += state.electoralVotes; return { ...state, cumulativeVotes }; }); stackedData.push({model, data: cumulativeData}); }); return stackedData; }3b:T1aa0,function GaugeChart() { var pi = Math.PI, rad = pi/180, deg = 180/pi; var properties = { width: 800, height: 300, margin: 10, rotation: 0, thickness: 0.15, arc: 1, ticks: 5, color_scheme: "interpolateRdYlBu", color_step: 150, tick_color: "#FFFFFF", needle_color: "#000000" }; var needlePercent = 0, center = {}, radii = {}, angles = {}, ticks = {}, gradient = [], scales = {}; var setCenter = (function initCenter () { center.x = properties.width / 2, center.y = properties.height - properties.margin; return initCenter; })(); var setRadii = (function initRadii () { var base = properties.height - (2 * properties.margin); radii.base = base, radii.cap = base / 15, radii.inner = base * (1 - properties.thickness), radii.outer_tick = base + 5, radii.tick_label = base + 15; return initRadii; })(); var setAngles = (function initAngles () { var arc_complement = 1 - properties.arc; angles.arc_complement = arc_complement, angles.start_angle = (-pi/2) + (pi * arc_complement / 2) + (properties.rotation * rad), angles.end_angle = (pi/2) - (pi * arc_complement / 2) + (properties.rotation * rad); return initAngles; })(); var setTicks = (function initTicks () { var sub_arc = (angles.end_angle - angles.start_angle) / (properties.ticks - 1), tick_pct = 100 / (properties.ticks - 1); ticks = d3.range(properties.ticks).map(function(d) { var sub_angle = angles.start_angle + (sub_arc * d); return { label: (tick_pct * d).toFixed(0) + '%', angle: sub_angle, coordinates: [[sub_angle, radii.inner], [sub_angle, radii.outer_tick]] } }); return initTicks; })(); var setGradient = (function initGradient () { // If `properties.color_scheme` is a D3 color interpolator, use it directly // Otherwise, assume it's a custom function (like d3.scaleLinear() or d3.scaleOrdinal()) var c = typeof properties.color_scheme === 'function' ? properties.color_scheme : d3[properties.color_scheme], samples = properties.color_step, total_arc = angles.end_angle - angles.start_angle, sub_arc = total_arc / samples; gradient = d3.range(samples).map(function(d) { var sub_color = d / (samples - 1), sub_start_angle = angles.start_angle + (sub_arc * d), sub_end_angle = sub_start_angle + sub_arc; return { fill: c(sub_color), // Apply color based on the current sample start: sub_start_angle, end: sub_end_angle }; }); return initGradient; })(); var setScales = (function initScales () { scales.lineRadial = d3.lineRadial(); scales.subArcScale = d3.arc() .innerRadius(radii.inner + 1) .outerRadius(radii.base) .startAngle(d => d.start) .endAngle(d => d.end); scales.needleScale = d3.scaleLinear() .domain([0, 1]) .range([angles.start_angle, angles.end_angle]); return initScales; })(); function updateValues () { setCenter(); setRadii(); setAngles(); setTicks(); setGradient(); setScales(); } var GaugeChart = {}; GaugeChart.setProperties = function(params) { Object.keys(params).map(function(d) { if (d in properties) properties[d] = params[d]; else throw new Error('One or more parameters not accepted.'); }); updateValues(); } GaugeChart.getProperties = function () { return properties; } GaugeChart.debug = function () { return { needlePercent, properties, center, radii, angles, ticks, gradient, svg }; } GaugeChart.setPercentage = function (pct) { needlePercent = pct; } GaugeChart.draw = function () { var svg = d3.create("svg") .attr("viewBox", [0, 0, properties.width, properties.height]); var gauge = svg.append("g") .attr("transform", `translate(${center.x}, ${center.y})`) .attr("class", "gauge-container"); // Draw arcs for the color gradient gauge.append("g") .attr("class", "gauge-arc") .selectAll("path") .data(gradient) .enter() .append("path") .attr("d", scales.subArcScale) .attr("fill", d => d.fill) .attr("stroke-width", 0.5) .attr("stroke", d => d.fill); // Draw ticks gauge.append("g") .attr("class", "gauge-ticks") .selectAll("path") .data(ticks) .enter() .append("g") .attr("class", "tick") .append("path") .attr("d", d => scales.lineRadial(d.coordinates)) .attr("stroke", properties.tick_color) .attr("stroke-width", 2) .attr("stroke-linecap", "round") .attr("fill", "none"); gauge.select("g.gauge-ticks") .selectAll("text") .data(ticks) .enter() .append("g") .attr("class", "tick-label") .append("text") .attr("transform", d => `translate(${radii.tick_label * Math.sin(d.angle)}, ${-radii.tick_label * Math.cos(d.angle)}) rotate(${d.angle * deg - pi})`) .attr("dy", "0em") .attr("text-anchor", "middle") .attr("font-size", "1.25em") .attr("font-family", "helvetica") .attr("fill", "#333") .text(d => d.label); // Draw the needle gauge.append("g") .attr("class", "needle") .selectAll("path") .data([needlePercent]) .enter() .append("path") .attr("d", d => scales.lineRadial([[0,0], [scales.needleScale(d), radii.outer_tick]])) .attr("stroke", properties.needle_color) .attr("stroke-width", 6) .attr("stroke-linecap", "round"); // Draw the needle cap gauge.select("g.needle") .append("circle") .attr("cx", 0) .attr("cy", 0) .attr("r", radii.cap) .attr("stroke", properties.needle_color) .attr("stroke-width", 6) .style("fill", "white"); // Add text at the tip of the needle to display the percentage gauge.append("text") .attr("class", "needle-percentage") .attr("x", scales.needleScale(needlePercent) * Math.sin(scales.needleScale(needlePercent))) .attr("y", -scales.needleScale(needlePercent) * Math.cos(scales.needleScale(needlePercent))) .attr("dy", "2em") // Adjust position slightly above the needle tip .attr("text-anchor", "middle") .attr("font-size", "1.5em") .attr("font-family", "helvetica") .attr("fill", "#333") .attr("font-weight", "bold") .text(`${(needlePercent * 100).toFixed(1)}%`); // Display percentage with one decimal return svg; } return GaugeChart; };3c:Td69,html` 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gaugechart.getProperties().width, size.h + 2 * props.margin]);\n gauge_object.attr(\"transform\", `translate(${props.width / 2}, ${-size.y + props.margin})`);\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1161,"value":"","pinned":false,"hidden":false,"mode":"md"},{"id":1021,"value":"viewof map_type = radio({\n options: [\n { label: 'Together', value: 'Together' },\n { label: 'Broken', value: 'Broken' }\n ],\n value: 'Together'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1019,"value":"viewof shade_by = radio({\n options: [\n { label: '538', value: '538' },\n { label: 'JHK', value: 'JHK' },\n { label: 'DDHQ', value: 'DDHQ' },\n { label: 'RWH', value: 'RWH' }\n ],\n value: '538'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1016,"value":"legend_swatch = legend({\n color: d3.scaleLinear([0, 0.5, 1], [\"#ea5353\", \"#fafafa\", \"#3487e0\"]),\n title: \"Harris Odds of Winning\",\n tickFormat: \"%\",\n tickSize: 0,\n height: 44,\n width: width / 3\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":1023,"value":"tilegram = make_tilegram()","pinned":false,"hidden":false,"mode":"ojs"},{"id":620,"value":"","pinned":false,"hidden":false,"mode":"md"},{"id":1318,"value":"viewof models = radio({\n options: [\n { label: 'All Models', value: 'All Models' },\n { label: 'Model Avg.', value: 'Model Avg.' }\n ],\n value: 'All Models'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":990,"value":"viewof competitive = radio({\n options: [\n { label: 'All States', value: 'All States' },\n { label: 'Competitive', value: 'Competitive' }\n ],\n value: 'All States'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":893,"value":"stateLegend = legend({\n color: d3.scaleLinear([0, 0.5, 1], [\"#ea5353\", \"#fafafa\", \"#3487e0\"]),\n title: \"Harris Odds of Winning\",\n tickFormat: \"%\",\n tickSize: 0,\n height: 44,\n width: width / 3\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":783,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":630,"value":"","pinned":false,"hidden":false,"mode":"md"},{"id":1220,"value":"viewof models_table = radio({\n options: [\n { label: 'All Models', value: 'All Models' },\n { label: 'Model Avg.', value: 'Model Avg.' }\n ],\n value: 'All Models'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1294,"value":"viewof competitive_table = radio({\n options: [\n { label: 'All States', value: 'All States' },\n { label: 'Competitive', value: 'Competitive' }\n ],\n value: 'All States'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":82,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1360,"value":"","pinned":false,"hidden":false,"mode":"md"},{"id":1537,"value":"viewof x_axis = radio({\n title: \"X-Axis\",\n options: [\n { label: '538', value: '538' },\n { label: 'JHK', value: 'JHK' },\n { label: 'DDHQ', value: 'DDHQ' },\n { label: 'RWH', value: 'RWH' },\n { label: 'Model Avg.', value: 'Model Avg.' }\n ],\n value: '538'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1543,"value":"viewof y_axis = radio({\n title: \"Y-Axis\",\n options: [\n { label: 'JHK', value: 'JHK' },\n { label: 'DDHQ', value: 'DDHQ' },\n { label: 'RWH', value: 'RWH' },\n { label: '538', value: '538' },\n { label: 'Model Avg.', value: 'Model Avg.' }\n ],\n value: 'JHK'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1370,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":2186,"value":"","pinned":false,"hidden":false,"mode":"html"},{"id":2191,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":126,"value":"","pinned":false,"hidden":false,"mode":"md"},{"id":2193,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":97,"value":"electionColorScale = d3.scaleLinear()\n .domain([0, 0.4, 0.5, 0.6, 1])\n .range([\"#e84343\", \"#f8ebeb\", \"#fafafa\", \"#e6eef7\", \"#0b70db\"]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":1731,"value":"harrisColorScale = d3.scaleLinear()\n .domain([0.5, 0.7, 0.8, 0.9, 1])\n .range([\"#fafafa\", \"#e6eef7\", \"#b6d4f1\", \"#6ca8e7\", \"#0b70db\"]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":1734,"value":"trumpColorScale = d3.scaleLinear()\n .domain([0.5, 0.7, 0.8, 0.9, 1])\n .range([\"#fafafa\", \"#f8ebeb\", \"#f5c6c6\", \"#ef8b8b\", \"#e84343\"]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":812,"value":"isCompetitive = d => d.ModelAvg > 0.15 && d.ModelAvg < 0.85;","pinned":false,"hidden":false,"mode":"ojs"},{"id":1033,"value":"height = 0.625 * width","pinned":false,"hidden":false,"mode":"ojs"},{"id":1025,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":1060,"value":"info_map = {\n let info_map = new Map();\n mergedData.forEach(function(o) {\n let fips = o.FIPS;\n \n // Skip if FIPS is undefined\n if (fips !== null && !o.State.includes(\"Cd\")) {\n let name = o.State;\n let abbr = o.Abbreviation;\n let electoralVotes = o.electoralVotes;\n let FTE = o.FTE;\n let Standard = o.Standard;\n let DDHQ = o.DDHQ;\n let RWH = o.RWH;\n \n info_map.set(fips, {\n name: name,\n abbr: abbr,\n electoralVotes: electoralVotes,\n FTE: FTE,\n Standard: Standard,\n DDHQ: DDHQ,\n RWH: RWH,\n });\n }\n });\n return info_map;\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":1037,"value":"broken_tile_boundaries = {\n let map_file = await FileAttachment(\n \"new_electoral_broken_tile_boundaries.topo.json\"\n ).json();\n let boundaries = topojson.feature(map_file, map_file.objects.tiles);\n return boundaries;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1048,"value":"broken_tiles = {\n let map_file = await FileAttachment(\n \"new_electoral_broken_tiles.topo.json\"\n ).json();\n let states = topojson.feature(map_file, map_file.objects.tiles);\n return states;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1044,"value":"tile_boundaries = {\n let map_file = await FileAttachment(\n \"new_electoral_boundary_tiles.topo-2.json\"\n ).json();\n let boundaries = topojson.feature(map_file, map_file.objects.tiles);\n return boundaries;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1040,"value":"tiles = {\n let map_file = await FileAttachment(\"new_electoral_tiles.topo-1.json\").json();\n let states = topojson.feature(map_file, map_file.objects.tiles);\n return states;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1658,"value":"electionData = (await FileAttachment(\"pres24_scrape_stateodds_output@73.csv\").csv())\n .map(d => {\n const values = [+d.FTE, +d.Standard, +d.DDHQ, +d.RWH];\n // Sort the values to find the median\n values.sort((a, b) => a - b);\n \n // Calculate the median manually\n const middle = Math.floor(values.length / 2);\n const median = values.length % 2 === 0 ? (values[middle - 1] + values[middle]) / 2 : values[middle];\n \n return {\n ...d,\n ModelAvg: median\n };\n })\n .sort((a, b) => b.ModelAvg - a.ModelAvg);","pinned":false,"hidden":false,"mode":"ojs"},{"id":252,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":233,"value":"mergedData = electionData.map(d => {\n const electoralVote = electoralVotes.find(ev => ev.state === d.State);\n return {\n ...d,\n electoralVotes: electoralVote ? electoralVote.votes : 0\n };\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":258,"value":"bucketOrder = [\n \"0-10%\", \"10-20%\", \"20-30%\", \"30-40%\", \"40-50%\",\n \"50-60%\", \"60-70%\", \"70-80%\", \"80-90%\", \"90-100%\"\n];","pinned":false,"hidden":false,"mode":"ojs"},{"id":509,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":403,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":1904,"value":"silver_odds = 0.50","pinned":false,"hidden":false,"mode":"ojs"},{"id":2134,"value":"economist_odds = 0.56","pinned":false,"hidden":false,"mode":"ojs"},{"id":1974,"value":"model_avg = electionData.filter(d => d.State === 'Electoral College')\n .map(d => (\n (parseFloat(d.FTE) || 0) + \n (parseFloat(d.Standard) || 0) + \n (parseFloat(d.DDHQ) || 0) + \n (parseFloat(d.RWH) || 0) +\n (parseFloat(silver_odds) || 0) +\n (parseFloat(economist_odds) || 0)\n ) / 6)[0].toFixed(3);\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":914,"value":"tooltip = d3.select(\"body\").append(\"div\")\n .attr(\"class\", \"tooltip\")\n .style(\"background-color\", \"#f9f9f9\")\n .style(\"border\", \"1px solid #ccc\")\n .style(\"padding\", \"10px\")\n .style(\"position\", \"absolute\")\n .style(\"visibility\", \"hidden\")\n .style(\"font-family\", \"Georgia, serif\")\n .style(\"font-size\", \"14px\")\n .style(\"pointer-events\", \"none\");","pinned":false,"hidden":false,"mode":"ojs"},{"id":1802,"value":"function autoHeight(el) {\n var box = el.getBBox();\n return { y: box.y, h: box.height }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1925,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs"},{"id":1051,"value":"import { legend, swatches } from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":723,"value":"import {select, radio} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":120,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs"},{"id":1124,"value":"style = html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":1057,"value":"tippy = require(\"tippy.js@6\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":1054,"value":"topojson = require(\"topojson-client@3\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"d3 = require(\"d3@7\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W3d","stdlib":"1","titling":"auto"}

2024 Presidential Election Forecasts

2024 Presidential Election Needle

2024 Presidential Electoral Map

Path to 270

State Odds

Correlation Plot

Expected Correct Calls

Data and Code