31:T451,md`## County Map Here are the cumulative confirmed & probable cases and deaths for each county and the city of Detroit. On ${d3.timeFormat('%B %e')(new Date(sliderDate))}, **${d3.sum(data, ([key,value]) => counties.includes(key) && value['Cases'] > 0)}** out of 83 counties had a confirmed case and **${d3.sum(data, ([key,value]) => counties.includes(key) && value['Deaths'] > 0)}** counties had a confirmed death. You can also see where the hotspots were for the previous week by examining the weekly percent change in cases. For a more detailed map, using aggregated non-public case-level data, visit https://covidmapping.org where you can search for cases by address, zip or city. **Note**: City of Detroit and Wayne County are reported separately. Case data for the most recent dates have not been fully counted and are usually an undercount of the true value since there is a lag in reported cases. This affects a metric like hot spots indicating a decrease when in reality, all cases have not been accounted for. A better guide would be to look at the % change from 4-5 days ago. `32:T122e,choropleth = { const svg = d3.create("svg").attr("viewBox", [0, 40, 700, 360]); let dateofRecord = daily.filter(d => +d.date === sliderDate)[0] const totalCases = dateofRecord['totalCases'] const totalDeaths = dateofRecord['totalDeaths'] const totalPop = d3.sum(Object.values(pop), d => d) const legends = [ legend({color: colorScale, title: `Cumulative Cases (N = ${d3.format(',')(totalCases)})`, tickFormat: ',', width: 180}), legend({color: colorScale, title: `Cumulative Deaths (N = ${d3.format(',')(totalDeaths)})`, tickFormat: ',', width: 180}), legend({color: colorScaleRCase, title: `Case rate per 100k (MI = ${d3.format('.0f')(totalCases/totalPop*100e3)})`, width: 180, tickFormat: ""}), legend({color: colorScaleRDeath, title: `Death rate per 100k (MI = ${d3.format('.0f')(totalDeaths/totalPop*100e3)})`, width: 180, tickFormat: ""}), legend({color: colorScaleHotSpot, title: `Weekly % change in cases`, width: 180, tickFormat: ".0%"}) ] svg.selectAll('.legend') .data(legends) .join('g') .attr('class', (d,i) => `legend ${i == 0 ? 'cases' : i == 1 ? 'deaths off' : i == 2 ? 'rcase off' : 'rdeath off'}`) .attr("transform", "translate(0,330)") .append(d => d) svg.append("g") .selectAll("path") .data(geojson.features) .join("path") .attr('class', 'county') .attr("fill", d => data.get(d.properties.NAME) ? colorScale(data.get(d.properties.NAME)['cases']) : colorScale(0)) .attr("d", path) .attr('stroke', 'white') .attr('stroke-width', 1) const tooltipData = d => { let place = d.properties.NAME; let text = `${place}\nCases: ${data.get(place) ? numFmt(data.get(place)['Cases']) : 0}` if (data.get(place)) { text += `\nDeaths: ${numFmt(data.get(place)['Deaths'])} Case rate per 100k: ${d3.format('.0f')(data.get(place)['Case Rate'])} Death rate per 100k: ${d3.format('.0f')(data.get(place)['Death Rate'])} Weekly change: ${isNaN(data.get(place)['ChangePct']) ? '--%' : d3.format('.0%')(data.get(place)['ChangePct'])} (${d3.format('.0f')(data.get(place)['Previous Period'])} → ${d3.format('.0f')(data.get(place)['Past Period'])})` } return text } const updateTip = (g, value) => { if (!value) return g.style("display", "none"); g.style("display", null) .style("pointer-events", "none") .style("font", "10px sans-serif"); const xpos = 10, ypos = 220; const text = tooltip.selectAll("text") .data([null]) .join("text") .attr("transform", `translate(${xpos},${ypos})`) .call(text => text .selectAll("tspan") .data((value + "").split(/\n/)) .join("tspan") .attr("x", (d,i) => i ? 5 : 0) .attr("y", (_,i) => `${i * 1.1}em`) // line spacing .style("font-weight", (_,i) => i ? null : "bold") // bolds title .text(d => d)); const {x, y, width: w, height: h} = text.node().getBBox(); const rect = tooltip.selectAll('rect') .data([null]) .join('rect') .attr("fill", "none") .attr("stroke", "#045a8d") .attr('x', xpos-5) .attr('y', ypos-15) .attr('width', w+10) .attr('height', h+10) } const tooltip = svg.append("g") svg.selectAll(".county") .on("mouseover", function(d) { tooltip.call(updateTip, tooltipData(d)); d3.select(this).raise().attr('stroke', 'black') }) .on("mouseout", function(d) { tooltip.call(updateTip, null); d3.select(this).lower().attr('stroke', 'white'); }) function transitionMap(radio1, scale, k) { svg.selectAll('.county')//.transition().duration(T) .attr("fill", d => data.get(d.properties.NAME) ? scale(data.get(d.properties.NAME)[radio1]) : radio1 !== "Hot Spots" ? scale(0) : '#eee' ) svg.selectAll('.legend').classed('off', (d,i) => i == k ? false : true) //tooltip.call(updateTip, tooltipData(d.properties.NAME)) } function update(radio1) { radio1 === "Cases" ? transitionMap(radio1, colorScale, 0) : radio1 === "Deaths" ? transitionMap(radio1, colorScale, 1) : radio1 === "Case Rate" ? transitionMap(radio1, colorScaleRCase, 2) : radio1 === "Death Rate" ? transitionMap(radio1, colorScaleRDeath, 3) : transitionMap(radio1, colorScaleHotSpot, 4) } return Object.assign(svg.node(), {update}); }33:T741,countyChart = { let margin = ({top: 20, right: 20, bottom: 0, left: 50}), W = 700, H = 120, width = W - margin.left - margin.right, height = H - margin.top - margin.bottom; const svg = d3.create("svg") .attr("viewBox", [0, 0, W, H]); let x = d3.scaleLinear() .domain([0, 1]) .range([margin.left, width - margin.right]); let y = d3.scaleBand() .domain(topCounties.map(d => d.Category).reverse()) .range([height - margin.bottom, margin.top]) .padding(0.1); svg.selectAll("g") .data(topCountySeries) .join("g") .attr("fill", d => countyColor(d.key)) .selectAll('rect') .data(d => d) .join('rect') .attr("class", "hbar") .attr("x", d => x(d[0])) .attr("y", (d,i) => y(d.data.Category)) .attr("width", d => x(d[1]) - x(d[0])) .attr("height", y.bandwidth()) let xAxis = g => g .attr("transform", `translate(0,${margin.top})`) .call(d3.axisTop(x).ticks(10, "%")) .call(g => g.selectAll(".domain").remove()) let yAxis = g => g .attr("transform", `translate(${margin.left},0)`) .call(d3.axisLeft(y).tickSizeOuter(0)) .call(g => g.selectAll(".domain").remove()) svg.append("g") .call(xAxis); svg.append("g") .call(yAxis); const tooltipData = d => { return `${d.key}: ${d3.format(',')(d.data[d.key])}` } const tooltip = svg.append("g"); svg.selectAll(".hbar") .on("mouseover", function(d) { tooltip.call(callout, tooltipData(d)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); d3.select(this).attr('stroke', 'black') }) .on("mouseout", function(d) { tooltip.call(callout, null); d3.select(this).attr('stroke', "none"); }) return svg.node(); }34:T1413,dailyChart = { const height = 210; const margin = {left: 160, top: 0, right: 200, bottom: 20}; const svg = d3.create("svg") .attr("viewBox", [-margin.left, 0, width, height+margin.bottom]) let x = d3.scaleTime() .domain([d3.min(daily, d => d.date), d3.timeDay.offset(d3.max(daily, d=> d.date))]) .range([0, width - margin.right]) let y = d3.scaleLinear() .domain([0, 10500]).nice() .range([height, 0]) let xAxis = d3.axisBottom(x).ticks(9).tickSizeOuter(0), yAxis = d3.axisRight(y).ticks(5) let [minDate, maxDate] = d3.extent(daily, d => d.date) svg.append("g") .selectAll(".bar") .data(daily) .join("rect") .attr('class', 'bar') .attr('x', d => x(d3.timeHour.offset(d.date))) .attr('y', d => y(d.cases)) .attr('width', x(79200*1000)-x(0)) .attr('height', d => height - y(d.cases)) .attr('fill', '#FFCB05') .attr('opacity', 0.3) svg.append('g') .attr('class', 'x-axis') .attr('transform', `translate(0,${height})`) .call(xAxis) svg.append('g') .attr('class', 'y-axis') .attr('transform', `translate(${width - margin.right},0)`) .call(yAxis) svg.select('.y-axis .domain').remove() // Moving average section let mvAvgLine = d3.line() .curve(d3.curveCardinal) .x(d => x(d.key)) .y(d => y(d.avg)) let avgLine = svg.append('path') .datum(movingAverage(daily, 'cases', 7)) .attr('class', 'avgLine') .attr('d', mvAvgLine) const xlegend = x(new Date(2020,9,25)), ylegend = height - 20; svg.append('line') .attr('class', 'avgLine') .attr('x1', xlegend) .attr('x2', xlegend+25) .attr('y1', ylegend) .attr('y2', ylegend) svg.append('text') .attr('x', xlegend+35) .attr('y', ylegend) .attr('dy', '0.35em') .text('7-day average') // Annotation section svg.selectAll('.milestone') .data(annotations) .join('line').lower() .attr('class', 'milestone') .attr('x1', d => x(d3.timeHour.offset(d.date,12))) .attr('x2', d => x(d3.timeHour.offset(d.date,12))) .attr('y1', d => y(daily[d3.timeDay.count(minDate,d.date)]['cases']) - 5) .attr('y2', d => { return grps.get(+d.date).length > 1 ? d.y1+15 : d.y1 }) svg.selectAll('.milestone-text') .data(annotations) .join('text') .attr('class', d => `milestone-text ${d.end ? 'end' : ''}`) .attr('x', d => x(d3.timeHour.offset(d.date,12))) .attr('y', d => d.y1 - 5) .text(d => d.annotation) // Annotation section svg.append('rect').lower() .attr('x', x(new Date(2020,2,24))) .attr('width', x(new Date(2020,5,2)) - x(new Date(2020,2,24))) .attr('height', height) .attr('fill', '#f1f3ff') svg.append('text') .attr('x', x(new Date(2020,2,26))) .attr('y', 15) .text('Stay Home, Stay Safe') svg.append('rect').lower() .attr('x', x(new Date(2020,10,18))) .attr('width', x(new Date(2021,1,1)) - x(new Date(2020,10,18))) .attr('height', height) .attr('fill', '#f1f3ff') svg.append('text') .attr('x', x(new Date(2020,10,20))) .attr('y', 15) .text('Pause to Save Lives') const tooltipData = d => { return `${d3.timeFormat('%b %e')(d.date)} ${numFmt(d.cases)} cases ${d.deaths} deaths` } const tooltip = svg.append("g"); svg.selectAll(".bar") .on("mouseover", function(d) { tooltip.call(callout, tooltipData(d), 0); tooltip.attr("transform",`translate(${d3.mouse(this)[0]-30},${d3.mouse(this)[1]})`); d3.select(this).attr('opacity', 1) }) .on("mouseout", function(d) { tooltip.call(callout, null, 0); d3.select(this).attr('opacity', 0.3); }) // Transition section function transitionDaily(dailyRadio) { if (dailyRadio == 'Cases') { y.domain([0, 10500]).nice() svg.selectAll('.bar').transition().duration(T).delay(500) .attr('y', d => y(d.cases)) .attr('height', d => height - y(d.cases)) svg.selectAll('.milestone') .transition().duration(T).delay(500) .attr('y1', d => y(daily[d3.timeDay.count(minDate,d.date)]['cases']) - 5 ) avgLine.datum(movingAverage(daily, 'cases', 7)) .transition().duration(T).delay(500) .attr('d', mvAvgLine) } else { y.domain([0, 220]).nice() svg.selectAll('.bar').transition().duration(T).delay(500) .attr('y', d => y(d.deaths)) .attr('height', d => height - y(d.deaths)) svg.selectAll('.milestone') .transition().duration(T).delay(500) .attr('y1', d => y(daily[d3.timeDay.count(minDate,d.date)]['deaths']) - 5 ) avgLine.datum(movingAverage(daily, 'deaths', 7)) .transition().duration(T).delay(500) .attr('d', mvAvgLine) } svg.select('.y-axis') //.transition().duration(500) .call(yAxis) } function updateDaily(dailyRadio) { transitionDaily(dailyRadio) } return Object.assign(svg.node(), {updateDaily}); }35:T73b,ageChart = { let margin = ({top: 20, right: 20, bottom: 0, left: 50}), W = 700, H = 120, width = W - margin.left - margin.right, height = H - margin.top - margin.bottom; const svg = d3.create("svg") .attr("viewBox", [0, 0, W, H]); let x = d3.scaleLinear() .domain([0, 1]) .range([margin.left, width - margin.right]); let y = d3.scaleBand() .domain(age.map(d => d.Category).reverse()) .range([height - margin.bottom, margin.top]) .padding(0.1); svg.selectAll("g") .data(ageSeries) .join("g") .attr("fill", d => ageColor(d.key)) .selectAll('rect') .data(d => d) .join('rect') .attr("class", "hbar") .attr("x", d => x(d[0])) .attr("y", (d,i) => y(d.data.Category)) .attr("width", d => x(d[1]) - x(d[0])) .attr("height", y.bandwidth()) let xAxis = g => g .attr("transform", `translate(0,${margin.top})`) .call(d3.axisTop(x).ticks(10, "%")) .call(g => g.selectAll(".domain").remove()) let yAxis = g => g .attr("transform", `translate(${margin.left},0)`) .call(d3.axisLeft(y).tickSizeOuter(0)) .call(g => g.selectAll(".domain").remove()) svg.append("g") .call(xAxis); svg.append("g") .call(yAxis); const tooltipData = d => { return `${d.key}: ${fmtPct(d.data[d.key])}` } const tooltip = svg.append("g"); svg.selectAll(".hbar") .on("mouseover", function(d) { tooltip.call(callout, tooltipData(d)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); d3.select(this).attr('stroke', 'black') }) .on("mouseout", function(d) { tooltip.call(callout, null); d3.select(this).attr('stroke', "none"); }) return svg.node(); }36:Tce7,ageRateChart = { const width = 500, height = 120, // Ref: https://censusreporter.org/profiles/04000US26-michigan/ miage = [1156194,1279583,1379573,1204044,1193666,1361439,1272037,745232,404147] const svg = d3.create("svg") .attr("viewBox", [-60, -20, width+330, height+40]) let x = d3.scaleBand() .domain(age.columns.slice(1)) .range([0, width]) .padding(0.2) let ymax = [totalCases,totalDeaths].map((total,row) => { return d3.max(Object.entries(age[row+1]).slice(1).map(([key,value],i) => 100000*value*total/miage[i])) }) let y = d3.scaleLinear() .domain([0, ymax[0]]).nice() .range([height, 0]) let xAxis = d3.axisBottom(x), yAxis = d3.axisRight(y).ticks(5), gridlines = d3.axisRight(y).ticks(5).tickSize(-width).tickFormat(""); svg.append("g") .selectAll(".bar") .data(age.columns.slice(1)) .join("rect") .attr('class', 'bar') .attr('x', d => x(d)) .attr('y', (d,i) => y(100000*age[1][d]*totalCases/miage[i])) .attr('width', x.bandwidth()) .attr('height', (d,i) => height - y(100000*age[1][d]*totalCases/miage[i])) .attr('fill', d => ageColor(d)) svg.append('g') .attr('class', 'x-axis') .attr('transform', `translate(0,${height})`) .call(xAxis) svg.append('g') .attr('class', 'y-axis') .attr('transform', `translate(${width},0)`) .call(yAxis) svg.append('g').lower() .attr('class', 'grid') .attr('transform', `translate(${width},0)`) .call(gridlines) svg.append('text') .attr('id', 'ylabel') .attr('transform', `translate(${width+35},5)`) .attr('font-size', '0.8em') .text('Cases per 1K') function transitionAgeRate(ageRadio) { if (ageRadio == 'Cases') { y.domain([0,ymax[0]]).nice() svg.select('#ylabel').text('Cases per 100K') svg.selectAll('.bar').transition().duration(T).delay(500) .attr('y', (d,i) => y(100000*age[1][d]*totalCases/miage[i])) .attr('height', (d,i) => height - y(100000*age[1][d]*totalCases/miage[i])) } else { y.domain([0,ymax[1]]).nice() svg.select('#ylabel').text('Deaths per 100K') svg.selectAll('.bar').transition().duration(T).delay(500) .attr('y', (d,i) => y(100000*age[2][d]*totalDeaths/miage[i])) .attr('height', (d,i) => height - y(100000*age[2][d]*totalDeaths/miage[i])) } svg.select('.y-axis').transition().duration(500).call(yAxis) svg.select('.grid').transition().duration(500).call(gridlines) } function updateAgeRate(ageRadio) { ageRadio == 'Cases' ? transitionAgeRate(ageRadio) : transitionAgeRate(ageRadio) const tooltipData = function(d,i) { let rate = ageRadio == 'Cases' ? age[1][d]*totalCases/miage[i] : age[2][d]*totalDeaths/miage[i] return numFmt(100000*rate) } const tooltip = svg.append("g"); svg.selectAll(".bar") .on("mouseover", function(d,i) { tooltip.call(callout, tooltipData(d,i)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); }) .on("mouseout", () => tooltip.call(callout, null)); } return Object.assign(svg.node(), {updateAgeRate}); }37:T4dd,md`## Race Breakdown of cumulative cases and deaths by race compared to the Census. Blacks or African Americans are disportionately affected with higher rates of deaths. Reasons given by public health officials include: - longstanding health inequities - disproportionately belong to the work force that does not have the luxury of working from home (i.e., low-wage essential workers) - less likely to be insured - more likely to have existing health conditions - face medical racial bias that prevents them from getting proper treatment - lack of adequate access to health care and experience high rates of poverty > *This virus is holding up a mirror to our society and reminding us of deep inequities in our country....From basic lack of access to health care, transportation, and protections in the workplace, these inequities hit people of color and vulnerable communities the hardest.* - Governor Gretchen Whitmer Here's a [Vox article](https://www.vox.com/identities/2020/4/10/21211920/detroit-coronavirus-racism-poverty-hot-spot) and [NY Times article](https://www.nytimes.com/2020/04/07/us/coronavirus-race.html) on the matter. **Note**: *Hispanic* has been added to the *Other* category in the Census breakdown. `38:T72b,raceChart = { let margin = ({top: 20, right: 20, bottom: 0, left: 50}), W = 700, H = 120, width = W - margin.left - margin.right, height = H - margin.top - margin.bottom; const svg = d3.create("svg") .attr("viewBox", [0, 0, W, H]); let x = d3.scaleLinear() .domain([0, 1]) .range([margin.left, width - margin.right]); let y = d3.scaleBand() .domain(race.map(d => d.Category).reverse()) .range([height - margin.bottom, margin.top]) .padding(0.1); svg.selectAll("g") .data(raceSeries) .join("g") .attr("fill", d => raceColor(d.key)) .selectAll('rect') .data(d => d) .join('rect') .attr("class", "hbar") .attr("x", d => x(d[0])) .attr("y", (d,i) => y(d.data.Category)) .attr("width", d => x(d[1]) - x(d[0])) .attr("height", y.bandwidth()) let xAxis = g => g .attr("transform", `translate(0,${margin.top})`) .call(d3.axisTop(x).ticks(10, "%")) .call(g => g.selectAll(".domain").remove()) let yAxis = g => g .attr("transform", `translate(${margin.left},0)`) .call(d3.axisLeft(y).tickSizeOuter(0)) .call(g => g.selectAll(".domain").remove()) svg.append("g") .call(xAxis); svg.append("g") .call(yAxis); const tooltipData = d => { return `${d.key}: ${fmtPct(d.data[d.key])}` } const tooltip = svg.append("g"); svg.selectAll(".hbar") .on("mouseover", function(d) { tooltip.call(callout, tooltipData(d)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); d3.select(this).attr('stroke', 'black') }) .on("mouseout", function(d) { tooltip.call(callout, null); d3.select(this).attr('stroke', "none"); }) return svg.node(); }39:Td51,raceRateChart = { const width = 500, height = 120, mirace = [1363183,7476047,324358+3290,46417,250796,14443+517381,1]; const svg = d3.create("svg") .attr("viewBox", [-60, -20, width+330, height+60]) let x = d3.scaleBand() .domain(race.columns.slice(1,7)) .range([0, width]) .padding(0.2) let ymax = [totalCases,totalDeaths].map((total,row) => { return d3.max(Object.entries(race[row+1]).slice(1,7).map(([key,value],i) => 100000*value*total/mirace[i])) }) let y = d3.scaleLinear() .domain([0, ymax[0]]).nice() .range([height, 0]) let xAxis = d3.axisBottom(x), yAxis = d3.axisRight(y).ticks(5).tickFormat(d3.format('~s')), gridlines = d3.axisRight(y).ticks(5).tickSize(-width).tickFormat(""); svg.append("g") .selectAll(".bar") .data(race.columns.slice(1,7)) .join("rect") .attr('class', 'bar') .attr('x', d => x(d)) .attr('y', (d,i) => y(100000*race[1][d]*totalCases/mirace[i])) .attr('width', x.bandwidth()) .attr('height', (d,i) => height - y(100000*race[1][d]*totalCases/mirace[i])) .attr('fill', d => raceColor(d)) .append('title') .text((d,i) => 100000*race[1][d]*totalCases/mirace[i]) svg.append('g') .attr('class', 'x-axis') .attr('transform', `translate(0,${height})`) .call(xAxis) svg.selectAll('g.x-axis g.tick text') .data(d3.range(6)) .attr('y', d => d%4 == 3 ? 21 : 9) svg.append('g') .attr('class', 'y-axis') .attr('transform', `translate(${width},0)`) .call(yAxis) svg.append('g').lower() .attr('class', 'grid') .attr('transform', `translate(${width},0)`) .call(gridlines) svg.append('text') .attr('id', 'ylabel') .attr('transform', `translate(${width+35},5)`) .attr('font-size', '0.8em') .text('Cases per 100K') function transitionRaceRate(raceRadio) { if (raceRadio == 'Cases') { y.domain([0,ymax[0]]).nice() svg.select('#ylabel').text('Cases per 100K') svg.selectAll('.bar').transition().duration(T).delay(500) .attr('y', (d,i) => y(100000*race[1][d]*totalCases/mirace[i])) .attr('height', (d,i) => height - y(100000*race[1][d]*totalCases/mirace[i])) } else { y.domain([0,ymax[1]]).nice() svg.select('#ylabel').text('Deaths per 100K') svg.selectAll('.bar').transition().duration(T).delay(500) .attr('y', (d,i) => y(100000*race[2][d]*totalDeaths/mirace[i])) .attr('height', (d,i) => height - y(100000*race[2][d]*totalDeaths/mirace[i])) } svg.select('.y-axis').transition().duration(500).call(yAxis) svg.select('.grid').transition().duration(500).call(gridlines) } function updateRaceRate(raceRadio) { transitionRaceRate(raceRadio) const tooltipData = function(d,i) { let rate = raceRadio == 'Cases' ? race[1][d]*totalCases/mirace[i] : race[2][d]*totalDeaths/mirace[i] return numFmt(100000*rate) } const tooltip = svg.append("g"); svg.selectAll(".bar") .on("mouseover", function(d,i) { tooltip.call(callout, tooltipData(d,i)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); }) .on("mouseout", () => tooltip.call(callout, null)); } return Object.assign(svg.node(), {updateRaceRate}); }3a:T6bc,ethnicityChart = { const earcs = pie(ethnicity); const svg = d3.create("svg") .attr("viewBox", [-35, -25, 200, 50]); svg.selectAll("path") .data(earcs) .join("path") .attr('class', 'ethnicitySlice') .attr("fill", d => ethnicityColor[d.index]) .attr("d", arc) svg.append("g") .attr("font-family", "sans-serif") .attr("font-size", '.2em') .attr("text-anchor", "middle") .selectAll("text") .data(earcs) .join("text") .attr("transform", d => `translate(${arc.centroid(d)})`) .call(text => text.append("tspan") .attr("x", (d, i) => i < 2 ? 0 : -3) .attr("y", (d, i) => i < 2 ? "-0.4em" : "0em") .attr("font-weight", 600) .text(d => d.data.Ethnicity)) .call(text => text.append("tspan") .attr('class', 'slices') .attr("x", (d, i) => i < 2 ? 0 : -3) .attr("y", (d, i) => i < 2 ? "0.7em" : "1.1em") .text(d => d.data.value == '<1%' ? d.data.value : d3.format('.0~%')(d.data.value))) function transitionEthnicity(genderRadio) { ethnicity.map(d => { d.value = genderRadio == "Cases" ? d.Cases : d.Deaths return d }) const enewpie = pie(ethnicity) svg.selectAll('.ethnicitySlice') .data(enewpie) .attr('d', arc) svg.selectAll('g text') .data(enewpie) .attr("transform", d => `translate(${arc.centroid(d)})`) svg.selectAll('text') .style('opacity', d => d.data.value == '<1%' ? 0 : 1) svg.selectAll('.slices') .text(d => d3.format('.0~%')(d.data.value)) } function update(genderRadio) { transitionEthnicity(genderRadio) } return Object.assign(svg.node(), {update}); }3b:T640,genderChart = { const arcs = pie(gender); const svg = d3.create("svg") .attr("viewBox", [-35, -25, 200, 50]); svg.selectAll("path") .data(arcs) .join("path") .attr('class', 'genderSlice') .attr("fill", d => genderColor[d.index]) .attr("d", arc) svg.append("g") .attr("font-family", "sans-serif") .attr("font-size", '.2em') .attr("text-anchor", "middle") .selectAll("text") .data(arcs) .join("text") .attr("transform", d => `translate(${arc.centroid(d)})`) .call(text => text.append("tspan") .attr("y", "-0.4em") .attr("font-weight", 600) .text(d => d.data.Gender)) .call(text => text.append("tspan") .attr('class', 'slices') .attr('x', 0) .attr("y", "0.7em") .text(d => d.data.value == '<1%' ? d.data.value : d3.format('.0~%')(d.data.value))) function transitionGender(genderRadio) { gender.map(d => { d.value = genderRadio == "Cases" ? d.Cases : d.Deaths return d }) const newpie = pie(gender) svg.selectAll('.genderSlice') .data(newpie) .attr('d', arc) svg.selectAll('g text') .data(newpie) .attr("transform", d => `translate(${arc.centroid(d)})`) svg.selectAll('text') .style('opacity', d => d.data.value == '<1%' || d.data.value < 0.005 ? 0 : 1) svg.selectAll('.slices') .text(d => d3.format('.0~%')(d.data.value)) } function updateGender(genderRadio) { transitionGender(genderRadio) } return Object.assign(svg.node(), {updateGender}); }3c:T741,statusChart = { let margin = ({top: 20, right: 20, bottom: 0, left: 50}), W = 700, H = 450, width = W - margin.left - margin.right, height = H - margin.top - margin.bottom; const svg = d3.create("svg") .attr("viewBox", [0, 0, W, H]); let x = d3.scaleLinear() .domain([0, 1]) .range([margin.left, width - margin.right]); let y = d3.scaleBand() .domain(status.map(d => d.Date)) .range([height - margin.bottom, margin.top]) .padding(0.1); svg.selectAll("g") .data(statusSeries) .join("g") .attr("fill", d => statusColor(d.key)) .selectAll('rect') .data(d => d) .join('rect') .attr("class", "hbar") .attr("x", d => x(d[0])) .attr("y", (d,i) => y(d.data.Date)) .attr("width", d => x(d[1]) - x(d[0])) .attr("height", y.bandwidth()) let xAxis = g => g .attr("transform", `translate(0,${margin.top})`) .call(d3.axisTop(x).ticks(10, "%")) .call(g => g.selectAll(".domain").remove()) let yAxis = g => g .attr("transform", `translate(${margin.left},0)`) .call(d3.axisLeft(y).tickSizeOuter(0)) .call(g => g.selectAll(".domain").remove()) svg.append("g").call(xAxis); svg.append("g").call(yAxis); const tooltipData = d => { return `${d.key}: ${numFmt(d.data[d.key])} (${fmtPct(d.data[d.key]/d.data.Cases)})` } const tooltip = svg.append("g"); svg.selectAll(".hbar") .on("mouseover", function(d) { tooltip.call(callout, tooltipData(d)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); d3.select(this).attr('stroke', 'black') }) .on("mouseout", function(d) { tooltip.call(callout, null); d3.select(this).attr('stroke', "none"); }) return svg.node(); }3d:T1aa5,caseGrowthChart = { const margin = {top: 0, right: 0, bottom: 30, left: 0}, width = 500, height = 250; let data = daily.filter(d => d.date >= dayReopen) const svg = d3.create("svg") .attr("viewBox", [-15, -20, width+330, height+40]) let x = d3.scaleTime() .domain([d3.timeDay.offset(dayReopen,-5), d3.max(data, d => d.date)]) .range([0, width]) let y1 = d3.scaleLog() .domain([200, 1000000]) .range([height, 0]) let y2 = d3.scaleLinear() .domain([0, 0.6]) .range([height, 0]) svg.append('text') .attr('id', 'yaxislabel') .attr('x', 50) .attr('dy', '-0.25em') .attr('font-size', '0.7em') svg.append('text') .attr('id', 'every2') .attr('font-size', '0.8em') .text('cases double every 2 days') svg.append('text') .attr('id', 'every40') .attr('font-size', '0.8em') .text('...every 40 days') svg.append('text') .attr('id', 'every30') .attr('font-size', '0.8em') .text('...every 30 days') svg.append('text') .attr('id', 'current') .attr('font-size', '0.8em') .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(data.slice(-1)[0].r7)) .attr('dx', 4) .attr('dy', '.2em') .text(`...every ${d3.format('.1f')(data.slice(-1)[0].dbl7)} days`) let xAxis = g => g .call(d3.axisBottom(x).ticks(6)) .call(g => g.select(".domain").remove()) let yAxis1 = d3.axisRight(y1) .tickValues([200,500,1000,2000,5000,10000,20000,50000,100000,200000,500000,1000000]) .tickSize(width - margin.left - margin.right) .tickFormat(d3.format(',d')) let yAxis2 = d3.axisRight(y2) .tickValues([0, 0.05, 0.1, 0.149, 0.189, 0.414, 0.5, 0.6]) .tickSize(width - margin.left - margin.right) .tickFormat(d3.format('.0~%')) let formatAxis = g => g .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick:not(:first-of-type) line") .attr("stroke-opacity", 0.2) .attr("stroke-dasharray", "2,4")) .call(g => g.selectAll(".tick text") .attr("x", 4) .attr("dy", -4)) let line1 = d3.line() .defined(d => d.value !== null) .x(d => x(d3.timeHour.offset(d.date))) .y(d => y1(d.value)) let line2 = d3.line() .defined(d => d.value !== null) .x(d => x(d3.timeHour.offset(d.date))) .y(d => y2(d.value)) svg.append("path") .datum(data) .attr('id', 'trendline') .attr('d', line2) .attr('stroke', '#00274C') .attr('stroke-width', 3) .attr('fill', 'none') svg.selectAll('circle') .data(data) .join('circle') .attr('cx', d => x(d3.timeHour.offset(d.date))) .attr('cy', d => y2(d.value)) .attr('r', 4) .attr('fill', '#00274C') .attr('opacity', 0) svg.append('g') .attr('transform', `translate(0,${height})`) .call(xAxis) let ylabel = svg.append('g') .attr('transform', `translate(${margin.left},0)`) .call(yAxis2) .call(formatAxis) let days = [2,40,30] svg.selectAll('.growthlines') .data(days.map(t => expGrowth(t, dayReopen, 'totalCases'))) .join('path').lower() .attr('class', 'growthlines') .attr('d', line1) .attr('fill', 'none') .attr('stroke', 'lightgray') function updateChart(radio2) { data.map(d => { d.value = radio2 == "cases" ? d.totalCasesRe : d.r7 return d }) let ease = d3.easeCubicInOut if (radio2 == "cases") { ylabel.call(yAxis1) .call(formatAxis) svg.selectAll('circle').transition().duration(T).ease(ease) .attr('cx', d => x(d3.timeHour.offset(d.date))) .attr('cy', d => y1(d.value)) svg.select("#trendline").transition().duration(T).ease(ease) .attr('d', line1) svg.selectAll('.growthlines') .data(days.map(t => expGrowth(t, dayReopen, 'totalCasesRe'))) .transition().duration(T).ease(ease) .attr('d', line1) svg.select('#every2').transition().duration(T).ease(ease) .attr('x', x(new Date(2020,5,25))) .attr('y', y1(300000)) .attr('dx', 0) svg.select('#every40').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y1(d3.max(expGrowth(40, dayReopen, 'totalCasesRe'), d => d.value))) svg.select('#every30').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y1(d3.max(expGrowth(30, dayReopen, 'totalCasesRe'), d => d.value))) svg.select('#current').transition().duration(T).ease(ease) .attr('opacity', 0) svg.select('#yaxislabel').text('cases since reopening') } else { ylabel.call(yAxis2) .call(formatAxis) svg.selectAll('circle').transition().duration(T).ease(ease) .attr('cx', d => x(d3.timeHour.offset(d.date))) .attr('cy', d => y2(d.value)) svg.select("#trendline").transition().duration(T).ease(ease) .attr('d', line2) svg.selectAll('.growthlines') .data(days.map(t => growthRate(t, dayReopen))) .transition().duration(T).ease(ease) .attr('d', line2) svg.select('#every2').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(d3.max(growthRate(2, dayReopen), d => d.value))) .attr('dx', 0) svg.select('#every30').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(d3.max(growthRate(30, dayReopen), d => d.value))) svg.select('#every40').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(d3.max(growthRate(40, dayReopen), d => d.value))) svg.select('#current').transition().duration(T).ease(ease) .attr('opacity', 1) svg.select('#yaxislabel').text('growth rate') } } function update(radio2) { updateChart(radio2) const tooltipData = d => { return `${dateFmt(d.date)}: ${radio2 === "cases" ? numFmt(d.totalCasesRe) + ' cases\n' + numFmt(d.totalDeathsRe) + ' deaths' : d3.format('.1%')(d.value)}` } const tooltip = svg.append("g"); svg.selectAll("circle") .on("mouseover", function(d) { tooltip.call(callout, tooltipData(d)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); d3.select(this).attr('opacity', 1) }) .on("mouseout", function(d) { tooltip.call(callout, null); d3.select(this).attr('opacity', 0); }) } return Object.assign(svg.node(), {update}); }3e:T1a38,deathGrowthChart = { const margin = {top: 20, right: 0, bottom: 30, left: 0}, width = 500, height = 250; let data = daily.filter(d => d.date >= dayReopen) const svg = d3.create("svg") .attr("viewBox", [-15, -30, width+330, height+50]) let x = d3.scaleTime() .domain([d3.timeDay.offset(dayReopen,-5), d3.max(data, d => d.date)]) .range([0, width]) let y1 = d3.scaleLog() .domain([20, 20000]) .range([height, 0]) let y2 = d3.scaleLinear() .domain([0, 0.6]) .range([height, 0]) svg.append('text') .attr('id', 'yaxislabel') .attr('x', 38) .attr('dy', '-0.25em') .attr('font-size', '0.7em') svg.append('text') .attr('id', 'every2') .attr('font-size', '0.8em') .text('deaths double every 2 days') svg.append('text') .attr('id', 'every60') .attr('font-size', '0.8em') .text('...every 60 days') svg.append('text') .attr('id', 'every40') .attr('font-size', '0.8em') .text('...every 40 days') svg.append('text') .attr('id', 'current') .attr('font-size', '0.8em') .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(data.slice(-1)[0].r7d)) .attr('dx', 4) .attr('dy', '.2em') .text(`...every ${d3.format('.1f')(data.slice(-1)[0].dbl7d)} days`) let xAxis = g => g .call(d3.axisBottom(x).ticks(5)) .call(g => g.select(".domain").remove()) let yAxis1 = d3.axisRight(y1) .tickValues([20,50,100,200,500,1000,2000,5000,10000,20000]) .tickSize(width - margin.left - margin.right) .tickFormat(d3.format(',d')) let yAxis2 = d3.axisRight(y2) .tickValues([0, 0.05, 0.1, 0.149, 0.19, 0.3, 0.414, 0.5, 0.6]) .tickSize(width - margin.left - margin.right) .tickFormat(d3.format('.0~%')) let formatAxis = g => g .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick:not(:first-of-type) line") .attr("stroke-opacity", 0.2) .attr("stroke-dasharray", "2,4")) .call(g => g.selectAll(".tick text") .attr("x", 4) .attr("dy", -4)) let line1 = d3.line() .defined(d => d.value !== null) .x(d => x(d3.timeHour.offset(d.date))) .y(d => y1(d.value)) let line2 = d3.line() .defined(d => d.value !== null) .x(d => x(d3.timeHour.offset(d.date))) .y(d => y2(d.value)) svg.append("path") .datum(data) .attr('id', 'trendline') .attr('d', line1) .attr('stroke', '#0174BB') .attr('stroke-width', 3) .attr('fill', 'none') svg.selectAll('circle') .data(data) .join('circle') .attr('cx', d => x(d3.timeHour.offset(d.date))) .attr('cy', d => y2(d.value)) .attr('r', 4) .attr('fill', '#0174BB') .attr('opacity', 0) svg.append('g') .attr('transform', `translate(0,${height})`) .call(xAxis) let ylabel = svg.append('g') .attr('transform', `translate(${margin.left},0)`) .call(yAxis2) .call(formatAxis) let days = [2,60,40] svg.selectAll('.growthlines') .data(days.map(t => expGrowth(t, dayReopen, 'totalDeaths'))) .join('path').lower() .attr('class', 'growthlines') .attr('d', line1) .attr('fill', 'none') .attr('stroke', 'lightgray') function updateChart(radio3) { data.map(d => { d.value = radio3 == "deaths" ? d.totalDeathsRe : d.r7d return d }) let ease = d3.easeCubicInOut if (radio3 == "deaths") { ylabel.call(yAxis1).call(formatAxis) svg.selectAll('circle').transition().duration(T).ease(ease) .attr('cy', d => y1(d.value)) svg.select("#trendline").transition().duration(T).ease(ease) .attr('d', line1) svg.selectAll('.growthlines') .data(days.map(t => expGrowth(t, dayReopen, 'totalDeathsRe'))) .transition().duration(T).ease(ease) .attr('d', line1) svg.select('#every2').transition().duration(T).ease(ease) .attr('x', x(new Date(2020,5,20))) .attr('y', y1(5000)) .attr('dx', 0) svg.select('#every60').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y1(d3.max(expGrowth(60, dayReopen, 'totalDeathsRe'), d => d.value))) svg.select('#every40').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y1(d3.max(expGrowth(40, dayReopen, 'totalDeathsRe'), d => d.value))) svg.select('#current').transition().duration(T).ease(ease) .attr('opacity', 0) svg.select('#yaxislabel').text('deaths since reopening') } else { ylabel.call(yAxis2).call(formatAxis) svg.selectAll('circle').transition().duration(T).ease(ease) .attr('cy', d => y2(d.value)) svg.select("#trendline").transition().duration(T).ease(ease) .attr('d', line2) svg.selectAll('.growthlines') .data(days.map(t => growthRate(t, dayReopen))) .transition().duration(T).ease(ease) .attr('d', line2) svg.select('#every2').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(d3.max(growthRate(2, dayReopen), d => d.value))) .attr('dx', 0) svg.select('#every60').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(d3.max(growthRate(60, dayReopen), d => d.value))) .attr('dy',-3) svg.select('#every40').transition().duration(T).ease(ease) .attr('x', x(d3.timeHour.offset(latestDate,6))) .attr('y', y2(d3.max(growthRate(40, dayReopen), d => d.value))) svg.select('#current').transition().duration(T).ease(ease) .attr('opacity', 1) svg.select('#yaxislabel').text('growth rate') } } function update(radio3) { updateChart(radio3) const tooltipData = d => { return `${dateFmt(d.date)}: ${radio3 === "deaths" ? numFmt(d.totalDeathsRe) + ' deaths\n' + numFmt(d.totalCasesRe) + ' cases' : d3.format('.1%')(d.value)}` } const tooltip = svg.append("g"); svg.selectAll("circle") .on("mouseover", function(d) { tooltip.call(callout, tooltipData(d)); tooltip.attr("transform",`translate(${d3.mouse(this)[0]},${d3.mouse(this)[1]})`); d3.select(this).attr('opacity', 1) }) .on("mouseout", function(d) { tooltip.call(callout, null); d3.select(this).attr('opacity', 0); }) } return Object.assign(svg.node(), {update}); }3f:T619,pop = { return {"Alcona": 10362, "Alger": 9097, "Allegan": 117327, "Alpena": 28360, "Antrim": 23365, "Arenac": 15041, "Baraga": 8320, "Barry": 61157, "Bay": 103923, "Benzie": 17753, "Berrien": 154141, "Branch": 43622, "Calhoun": 134487, "Cass": 51653, "Charlevoix": 26244, "Cheboygan": 25413, "Chippewa": 37517, "Clare": 30757, "Clinton": 79332, "Crawford": 13901, "Delta": 35857, "Dickinson": 25383, "Eaton": 109826, "Emmet": 33308, "Genesee": 406892, "Gladwin": 25337, "Gogebic": 15096, "Grand Traverse": 92573, "Gratiot": 40599, "Hillsdale": 45749, "Houghton": 36219, "Huron": 31166, "Ingham": 292735, "Ionia": 64210, "Iosco": 25081, "Iron": 11117, "Isabella": 70562, "Jackson": 158823, "Kalamazoo": 264870, "Kalkaska": 17824, "Kent": 653786, "Keweenaw": 2113, "Lake": 11881, "Lapeer": 88028, "Leelanau": 21764, "Lenawee": 98266, "Livingston": 191224, "Luce": 6283, "Mackinac": 10787, "Macomb": 874759, "Manistee": 24528, "Marquette": 66516, "Mason": 29100, "Mecosta": 43545, "Menominee": 22983, "Midland": 83209, "Missaukee": 15113, "Monroe": 150439, "Montcalm": 63968, "Montmorency": 9265, "Muskegon": 173588, "Newaygo": 48892, "Oakland": 1259201, "Oceana": 26625, "Ogemaw": 20952, "Ontonagon": 5795, "Osceola": 23341, "Oscoda": 8276, "Otsego": 24665, "Ottawa": 290494, "Presque Isle": 12738, "Roscommon": 23884, "Saginaw": 190800, "St. Clair": 159337, "St. Joseph": 61043, "Sanilac": 41182, "Schoolcraft": 8068, "Shiawassee": 68192, "Tuscola": 52516, "Van Buren": 75448, "Washtenaw": 370963, "Wayne": 1081231, "Wexford": 33466, "Detroit City": 672662} }40:T4c6,daily = { let daily = Array.from(d3.rollup(rawdata, v => ({ 'totalCases': d3.sum(v, d => d.Cases), 'cases': d3.sum(v, d => d.dailyCases), 'totalDeaths': d3.sum(v, d => d.Deaths), 'deaths': d3.sum(v, d => d.dailyDeaths), }), d => +d.Date), ([key,value]) => { value.date = new Date(key) return value }) const nthDate = 2 return daily.map((d,i,arr) => { const endIdx = Math.max(nthDate,i) const startIdx7 = Math.max(nthDate,i-7) const t7 = endIdx - startIdx7 const r7 = Math.exp(Math.log(arr[endIdx]['totalCases']/arr[startIdx7]['totalCases'])/t7)-1 d.r7 = i > nthDate ? r7 : 0 const dbl7 = 1/(Math.log(1+r7)/Math.log(2)) d.dbl7 = i > nthDate ? dbl7 : 0 const t7d = endIdx - startIdx7 const r7d = Math.exp(Math.log(arr[endIdx]['totalDeaths']/arr[startIdx7]['totalDeaths'])/t7d)-1 d.r7d = d.date > d3.timeDay.offset(dayOneDeath,3) ? r7d : 0 const dbl7d = 1/(Math.log(1+r7d)/Math.log(2)) d.dbl7d = d.date > d3.timeDay.offset(dayOneDeath,3) ? dbl7d : 0 d.value = d.totalCases d.totalCasesRe = d.totalCases - arr[91].totalCases d.totalDeathsRe = d.totalDeaths - arr[91].totalDeaths return d }) }41:T48f,data = { let MI = new Map let today = countyDaily.get(sliderDate) let N = 14 let refDate = past(N) let refDate2 = past(N*2) let omission = ['MDOC','FCI','Unknown','Out-of-State','Other','Not Reported'] today = today.filter(d => !omission.includes(d.County)) today.forEach(d => { let ratio = d['Cases']/refDate[d['County']]['Cases'] ratio = d3.max([ratio,1]) let pt1 = refDate[d['County']]['Cases'] let p1 = d3.max([d['Cases'] - pt1,0]) let pt2 = refDate2[d['County']]['Cases'] let p2 = d3.max([pt1 - pt2,0]) let p1p2 = p1 - p2 let p1p2ratio = p2 > 0 ? p1/p2 : undefined let p1p2pct = p2 > 0 ? (p1-p2)/p2 : undefined MI.set(d['County'], { 'Cases': d['Cases'], 'Deaths': d['Deaths'], 'Case Rate': d['Cases']/pop[d['County']]*100000, 'Death Rate': d['Deaths']/pop[d['County']]*100000, 'One Period Ago': pt1, 'Past Period': p1, 'Two Period Ago': pt2, 'Previous Period': p2, 'Change': p1p2, 'ChangeRatio': p1p2ratio, 'ChangePct': p1p2pct, 'Doubling Time': d['Cases'] >= 20 ? 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I've been tracking the Michigan data since March 21, 2020 and made this notebook to help make sense of it. I try to update this page monthly with data. \n\nBelow is a table summarizing how Michigan compares to the rest of the nation.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3865,"value":"html`\n \n \n \n \n \n \n

	Michigan Rank	Top State
Confirmed & Probable Cases	11th	California
Case Rate	35th	North Dakota
Confirmed & Probable Deaths	10th	California
Death Rate	17th	New Jersey
Population	10th	California

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3701,"value":"md`Source: [NYTimes](https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":847,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1563,"value":"viewof radio1 = radio({\n options: [\n {label: \"Hot Spots\", value: 'ChangePct'},\n {label: \"Cases\", value: 'Cases'},\n {label: \"Deaths\", value: 'Deaths'},\n {label: \"Case Rate\", value: 'Case Rate'},\n {label: \"Death Rate\", value: 'Death Rate'},\n ],\n value: 'ChangePct'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":4189,"value":"viewof sliderDate = Scrubber(daily.map(d => d.date.getTime()), {\n autoplay: false,\n alternate: true,\n delay: 100,\n initial: daily.length - 4,\n format: d => d3.timeFormat('%B %e')(new Date(d))\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":837,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":4001,"value":"md`Southeast Michigan particularly the tri-county area of Wayne, Oakland, and Macomb are the hardest hit areas in terms of cases (until November) and deaths accounting for a much larger share per person than the rest of the state.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3971,"value":"countyChartLegend = swatches({color: countyColor, marginLeft: 70})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3980,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":5409,"value":"md`I've also started a [county-focused notebook](https://observablehq.com/@caocscar/michigan-county-level-covid-19-data) that is meant to be complementary to this one.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":320,"value":"md`## Flattening the Curve\n\nHere are the number of new confirmed and probable cases (based on onset date) and deaths (date of death) along with the 7-day moving average.\n\nSome of the section below is outdated since the 2nd wave has hit Michigan.\n~~The peak for new cases based on the moving average occurred on April 1st, evidence pointing to the fact that social distancing is working.~~ Deaths lag behind cases so that's why we see the peak later in time. The curve has definitely seem to have flattened based on the stay-at-home order.\n\n~~There has been an uptick in cases after a brief lull in the number of cases since the stay-at-home order was lifted.~~\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2498,"value":"viewof dailyRadio = radio({\n options: [\n {label: \"Confirmed and Probable Cases\", value: 'Cases'},\n {label: \"Confirmed and Probable Deaths\", value: 'Deaths'},\n ],\n value: 'Cases'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":345,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":865,"value":"md`## Demographics\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":413,"value":"md`## Age \nAge breakdown of cumulative cases and deaths in 10-year intervals (except for 80+) compared to the age distribution from the Census.\n- cases are skewed towards older people compared to the population and deaths are even more heavily skewed than cases\n- the case rate shows people between 20 and 80 are getting COVID-19 at about the same rate\n- the death rate plot shows as age increases => the rate of people dying from coronavirus increases exponentially\n- curious to know how the age distribution for hospitalizations compare to cases and deaths\n- curious as how this would play out geographically (especially Detroit)\n\n\n**Note**: Values do not always add up to 100% because of rounding.\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":591,"value":"ageChartLegend = legend({title: \"Age Group\", color: ageColor, tickSize: 0, marginLeft: 70, width: 450})","pinned":false,"hidden":false,"mode":"ojs"},{"id":428,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":2267,"value":"viewof ageRadio = radio({\n options: [\n {label: \"Case Rate\", value: 'Cases'},\n {label: \"Death Rate\", value: 'Deaths'},\n ],\n value: 'Cases'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2211,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":2124,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":2343,"value":"raceChartLegend = swatches({color: raceColor, marginLeft: 70})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2349,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":2355,"value":"viewof raceRadio = radio({\n options: [\n {label: \"Case Rate\", value: 'Cases'},\n {label: \"Death Rate\", value: 'Deaths'},\n ],\n value: 'Cases'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2357,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":2131,"value":"md`## Ethnicity\nEthnicity breakdown for cumulative cases and deaths. The *unknown* category makes up a significant portion of cases (approx. one-quarter) and deaths (approx. one-seventh).\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2882,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":2776,"value":"viewof genderRadio = radio({\n options: [\n {label: \"Cases\", value: 'Cases'},\n {label: \"Deaths\", value: 'Deaths'},\n ],\n value: 'Cases',\n title: 'Ethnicity and Gender',\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":873,"value":"md`## Gender \nGender breakdown for cumulative cases and deaths. \n- Males are dying at a slightly higher rate compared to females even though they make a minority of confirmed cases.\n- [An early study](https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehaa373/5834647#203366008) suggests that a possible hypothesis is that men have a higher concentration of a particular enzyme (ACE2) than women that leads to increased vulnearability to *SARS-CoV-2*.\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2690,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs"},{"id":4606,"value":"md`## COVID Case Status\nA weekly breakdown of the confirmed cases-to-date by status.\n\nAbout ${fmtPct(statusActive)} of all confirmed cases are currently still active. Michigan has a case fatality rate of ${fmtPct(totalDeaths/totalCases)}. This does not account for asymptomic cases and probable cases that were never tested which would decrease the case fatality rate.\n\n\nNote: This chart will be updated every *Saturday* when MDHHS releases the **recovered** numbers.\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4611,"value":"breakdownLegend = swatches({color: statusColor, marginLeft: 70})","pinned":false,"hidden":false,"mode":"ojs"},{"id":4631,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs"},{"id":4654,"value":"md`\nHere's what each category represents:\n- **Hospitalized**: # of inpatients\n- **Infected**: # of people with confirmed diagnosis that does not fall into one of the other categories\n- **Recovered**: # of people with a confirmed COVID-19 diagnosis who are alive 30 days post-onset\n- **Deaths**: # of people who have died from a COVID-related cause\n\nPeople who currently have the coronavirus will fall into one of the first two categories (**hospitalized** or **infected**) while those who know longer have coronavirus will fall into one the latter two categories (**recovered** or **deaths**).\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":798,"value":"md`## Reopening on June 1st\n\nHere are the cumulative confirmed and probable cases on a log scale starting on June 1st when there were 307 cases. Michigan has been doubling our case count at a rate every ${d3.format('.1f')(d3.timeDay.count(dayReopen, latestDate)*Math.log(2)/Math.log(totalCasesRe/307))} days since reopening. \n\n~~Alternatively, you can view the average growth rate of COVID-19 for the past week (defined as the average daily percent increase since ${d3.timeFormat('%B %e')(d3.timeDay.offset(latestDate,-7))}). The formula for exponential growth of the coronavirus at the growth rate ${tex`r`}, for the past week (${tex`t=7`}) is \n${tex`x_t = x_0 (1+r)^t`} where ${tex`x_0`} is the number of cases a week ago and ${tex`x_t`} is the number of cases currently.~~ \n\nGraphic is inspired by this [NY Times article](https://www.nytimes.com/interactive/2020/03/21/upshot/coronavirus-deaths-by-country.html).\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1925,"value":"viewof radio2 = radio({\n options: [\n {label: \"Cumulative Cases\", value: 'cases'},\n //{label: \"Growth Rate (past 7 days)\", value: 'rate'}, \n ],\n value: 'cases'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1758,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs"},{"id":3568,"value":"md`Here is the same chart for cumulative deaths on a log scale starting on June 1st when there were 27 deaths. Michigan has been doubling our deaths at a rate every ${d3.format('.1f')(d3.timeDay.count(dayReopen, latestDate)*Math.log(2)/Math.log(totalDeathsRe/27))} days since reopening.\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3495,"value":"viewof radio3 = radio({\n options: [\n {label: \"Cumulative Deaths\", value: 'deaths'},\n // {label: \"Growth Rate (past 7 days)\", value: 'rate'}, \n ],\n value: 'deaths'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3486,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs"},{"id":878,"value":"md`

\n# Appendix\nThe section below contains some of the Observable code used to make the graphics on this page.\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":940,"value":"md`## Data`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4600,"value":"//status = d3.csv('https://caocscar-corsanywhere.herokuapp.com/https://docs.google.com/spreadsheets/d/e/2PACX-1vTMKsVgVrNMagP-IfMRkAwa96DSHo9zp2jcN_Rf5P4PuIs1necg2N4XCb9ARcdWRSzqTPrH4qFbEuwE/pub?gid=1610455648&single=true&output=csv', d3.autoType)\nstatus = d3.csvParse(await FileAttachment('covid - recovered@19.csv').text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":4602,"value":"statusSeries = d3.stack()\n .keys(status.columns.slice(1,-1))\n .order(d3.stackOrderNone)\n .offset(d3.stackOffsetExpand)(status)\n .map(d => (d.forEach(v => v.key = d.key), d)) // adds key to innermost array","pinned":false,"hidden":false,"mode":"ojs"},{"id":1031,"value":"gender = {\n //let gender = await d3.csv('https://cors-anywhere.herokuapp.com/https://docs.google.com/spreadsheets/d/e/2PACX-1vQIbi8OM3qCtsQmMWrpp_punQ7NxplpHQpM-Nx1Q9bttbFLEOo5W03AOhKRMbUID0yjD4-6d3ikjINY/pub?gid=1329572544&single=true&output=csv', d3.autoType)\n // let gender = d3.csvParse(await FileAttachment('covid - sex@6.csv').text(), d3.autoType)\n let gender = [\n {Gender: \"Female\", Cases: 0.51, Deaths: 0.46, value: 0.51},\n {Gender: \"Male\", Cases: 0.48, Deaths: 0.54, value: 0.48},\n {Gender: \"Unknown\", Cases: 0.01, Deaths: 0, value: 0.01},\n ];\n return gender;\n // gender.map(d => {\n // d.value = d.Cases\n // return d\n // })\n // return gender.slice(-3) // select last 3 rows\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2890,"value":"ethnicity = {\n //let ethnicity = await d3.csv('https://cors-anywhere.herokuapp.com/https://docs.google.com/spreadsheets/d/e/2PACX-1vQIbi8OM3qCtsQmMWrpp_punQ7NxplpHQpM-Nx1Q9bttbFLEOo5W03AOhKRMbUID0yjD4-6d3ikjINY/pub?gid=1200591266&single=true&output=csv', d3.autoType)\n //let ethnicity = d3.csvParse(await FileAttachment('covid - ethnicity@7.csv').text(), d3.autoType)\n let ethnicity = [\n {Ethnicity: \"Hispanic/Latino\", Cases: 0.0525, Deaths: 0.0314, value: 0.0525},\n {Ethnicity: \"Non-Hispanic Latino\", Cases: 0.6914, Deaths: 0.8351, value: 0.6914},\n {Ethnicity: \"Unknown\", Cases: 0.2561, Deaths: 0.1335, value: 0.2561},\n ];\n return ethnicity;\n // ethnicity.map(d => {\n // d.value = d.Cases\n // return d\n // })\n // return ethnicity.slice(-3) // select last 3 rows\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":6532,"value":"//age = d3.csv('https://cors-anywhere.herokuapp.com/https://docs.google.com/spreadsheets/d/e/2PACX-1vQIbi8OM3qCtsQmMWrpp_punQ7NxplpHQpM-Nx1Q9bttbFLEOo5W03AOhKRMbUID0yjD4-6d3ikjINY/pub?gid=1965538807&single=true&output=csv', d3.autoType)\n// age = d3.csvParse(await FileAttachment('covid - agestack@5.csv').text(), d3.autoType)\nage = {\n let data = [\n {'Category': \"Census\", '0-9': 0.116, '10-19': 0.128, '20-29': 0.138, '30-39': 0.121, '40-49': 0.119, '50-59': 0.136, '60-69': 0.127, '70-79': 0.075, '80+': 0.04},\n {'Category': \"Cases\", '0-9': 0.037, '10-19': 0.117, '20-29': 0.190, '30-39': 0.155, '40-49': 0.146, '50-59': 0.150, '60-69': 0.108, '70-79': 0.058, '80+': 0.039},\n {'Category': \"Deaths\", '0-9': 0, '10-19': 0.001, '20-29': 0.005, '30-39': 0.010, '40-49': 0.028, '50-59': 0.073, '60-69': 0.170, '70-79': 0.270, '80+': 0.444}\n ];\n const columns = Object.keys(data[0]);\n return Object.assign(data, { columns })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":449,"value":"ageSeries = d3.stack()\n .keys(age.columns.slice(1))\n .order(d3.stackOrderNone)\n .offset(d3.stackOffsetExpand)(age)\n .map(d => (d.forEach(v => v.key = d.key), d)) // adds key to innermost array","pinned":false,"hidden":false,"mode":"ojs"},{"id":2329,"value":"//race = d3.csv('https://cors-anywhere.herokuapp.com/https://docs.google.com/spreadsheets/d/e/2PACX-1vQIbi8OM3qCtsQmMWrpp_punQ7NxplpHQpM-Nx1Q9bttbFLEOo5W03AOhKRMbUID0yjD4-6d3ikjINY/pub?gid=2136403702&single=true&output=csv', d3.autoType)\n//race = d3.csvParse(await FileAttachment('covid - racestack@6.csv').text(), d3.autoType)\nrace = {\n let data = [\n {'Category': \"Census\", 'Black': 0.14, 'White': 0.75, 'Asian / Pacific Islander': 0.03, 'American Indian or Alaska Native': 0.01, 'Multiple': 0.03, 'Other': 0.05, 'Unknown': 0},\n {'Category': \"Cases\", 'Black': 0.120, 'White': 0.568, 'Asian / Pacific Islander': 0.015, 'American Indian or Alaska Native': 0.005, 'Multiple': 0.033, 'Other': 0.053, 'Unknown': 0.207},\n {'Category': \"Deaths\", 'Black': 0.214, 'White': 0.675, 'Asian / Pacific Islander': 0.011, 'American Indian or Alaska Native': 0.005, 'Multiple': 0.015, 'Other': 0.026, 'Unknown': 0.054}\n ]\n const columns = Object.keys(data[0]);\n return Object.assign(data, { columns })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2335,"value":"raceSeries = d3.stack()\n .keys(race.columns.slice(1))\n .order(d3.stackOrderNone)\n .offset(d3.stackOffsetExpand)(race)\n .map(d => (d.forEach(v => v.key = d.key), d)) // adds key to innermost array","pinned":false,"hidden":false,"mode":"ojs"},{"id":1249,"value":"$3f","pinned":false,"hidden":false,"mode":"ojs"},{"id":6249,"value":"daily[92]","pinned":true,"hidden":false,"mode":"ojs"},{"id":5523,"value":"$40","pinned":false,"hidden":false,"mode":"ojs"},{"id":3230,"value":"growthRateAvg = (data,N) => {\n return data.slice(3).map((row, idx, arr) => {\n const endIdx = idx\n const startIdx = Math.max(0, idx-N)\n const t = endIdx - startIdx\n const r = Math.exp(Math.log(arr[endIdx]['totalCases']/arr[startIdx]['totalCases'])/t)-1\n return idx > 0 ? r : 0\n });\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":4447,"value":"past = n => {\n let refDate = countyDaily.get(d3.max([+d3.timeDay.round(sliderDate-n*86400000),new Date(2020,2,15).getTime()]))\n let past = {}\n counties.forEach(d => past[d] = {'Cases': 0, 'Deaths': 0}) // initialize Object\n refDate.forEach(d => past[d.County] = {'Cases': d.Cases, 'Deaths': d.Deaths})\n return past\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":41,"value":"$41","pinned":false,"hidden":false,"mode":"ojs"},{"id":4156,"value":"countyDaily = d3.group(rawdata, d => +d.Date)","pinned":false,"hidden":false,"mode":"ojs"},{"id":4234,"value":"counties = geojson.features.map(d => d.properties.NAME).slice(0,83).sort()","pinned":false,"hidden":false,"mode":"ojs"},{"id":75,"value":"geojson = FileAttachment(\"mi_detroit.geojson\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":3911,"value":"topCounties = {\n let categories = ['Census','Cases','Deaths']\n let places = ['Detroit City','Wayne','Oakland','Macomb']\n let cases = places.reduce((a,b) => a + data.get(b)['Cases'], 0)\n let deaths = places.reduce((a,b) => a + data.get(b)['Deaths'], 0)\n let population = places.reduce((a,b) => a + pop[b], 0)\n let array = [], row;\n const totalCases = d3.sum(data, ([k,v]) => v['Cases'])\n const totalDeaths = d3.sum(data, ([k,v]) => v['Deaths'])\n\n for (let category of categories) {\n row = {}\n row['Category'] = category\n places.forEach(d => row[d] = category == 'Census' ? pop[d] : data.get(d)[category])\n row['All Other Counties'] = category == 'Census' ? d3.sum(Object.values(pop)) - population\n : category == 'Cases' ? totalCases - cases\n : totalDeaths - deaths;\n array.push(row)\n }\n array['columns'] = places.concat('All Other Counties')\n return array\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3951,"value":"topCountySeries = d3.stack()\n .keys(topCounties.columns)\n .order(d3.stackOrderNone)\n .offset(d3.stackOffsetExpand)(topCounties)\n .map(d => (d.forEach(v => v.key = d.key), d)) // adds key to innermost array","pinned":false,"hidden":false,"mode":"ojs"},{"id":5276,"value":"annotations = {\n let data = d3.csvParse(await FileAttachment(\"covid - timeline@11.csv\").text())\n return data.map(d => {\n d.date = parseTime(d.date)\n d.y1 = y2(+d.y1)\n d.end = +d.end\n return d\n })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":6415,"value":"y2 = d3.scaleLinear()\n .domain([0, 2200]).nice()\n .range([210, 0])","pinned":false,"hidden":false,"mode":"ojs"},{"id":5405,"value":"grps = d3.group(annotations, d => +d.date)","pinned":false,"hidden":false,"mode":"ojs"},{"id":5424,"value":"statusActive = {\n let lastDate = status[status.length-1]\n let pct = (lastDate['Hospitalized'] + lastDate['Infected'])/lastDate['Cases']\n return pct\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5460,"value":"rawdata = {\n //let rawdata = await d3.csv('https://cors-anywhere.herokuapp.com/https://docs.google.com/spreadsheets/d/e/2PACX-1vQIbi8OM3qCtsQmMWrpp_punQ7NxplpHQpM-Nx1Q9bttbFLEOo5W03AOhKRMbUID0yjD4-6d3ikjINY/pubhtml?gid=561444685&single=true', d3.autoType)\n let rawdata = d3.csvParse(await FileAttachment('covid - county@22.csv').text(), d3.autoType)\n rawdata = Array.from(d3.rollup(rawdata, v => ({\n 'Date': d3.timeParse('%m/%d/%Y')(v[0].Date),\n 'County': v[0].COUNTY.replace('St ','St. '),\n 'Cases': d3.sum(v, d => d['Cases.Cumulative']),\n 'Deaths': d3.sum(v, d => d['Deaths.Cumulative']),\n 'dailyCases': d3.sum(v, d => d['Cases']),\n 'dailyDeaths': d3.sum(v, d => d['Deaths']),\n }), d => d.Date, d => d.COUNTY), ([_,v]) => {\n return Array.from(v, ([_,value]) => value)\n })\n return rawdata.flat()\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":952,"value":"md`## Some Variables`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2004,"value":"viewof T = slider({\n min: 500, \n max: 1500, \n step: 50, \n value: 1000, \n title: \"Animation Time\", \n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":6097,"value":"dayReopen = new Date(2020,5,1)","pinned":false,"hidden":false,"mode":"ojs"},{"id":751,"value":"dayOne = new Date(2020,2,3)","pinned":false,"hidden":false,"mode":"ojs"},{"id":3433,"value":"dayOneDeath = new Date(2020,2,21)","pinned":false,"hidden":false,"mode":"ojs"},{"id":4175,"value":"earliestDate = d3.min(rawdata, d => d.Date)","pinned":false,"hidden":false,"mode":"ojs"},{"id":189,"value":"latestDate = d3.max(rawdata, d => d.Date)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2365,"value":"totalCases = d3.max(daily, d => d.totalCases)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2367,"value":"totalDeaths = d3.max(daily, d => d.totalDeaths)","pinned":false,"hidden":false,"mode":"ojs"},{"id":6193,"value":"totalCasesRe = totalCases - daily[91].totalCases","pinned":false,"hidden":false,"mode":"ojs"},{"id":6198,"value":"totalDeathsRe = totalDeaths - daily[91].totalDeaths","pinned":false,"hidden":false,"mode":"ojs"},{"id":2694,"value":"radius = 25","pinned":false,"hidden":false,"mode":"ojs"},{"id":1008,"value":"md`## HTML, CSS`","pinned":false,"hidden":false,"mode":"ojs"},{"id":987,"value":"html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":1578,"value":"html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":956,"value":"md`## Functions`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4919,"value":"callout = (g, value) => {\n if (!value) return g.style(\"display\", \"none\");\n\n g.style(\"display\", null)\n .style(\"pointer-events\", \"none\")\n .style(\"font\", \"10px sans-serif\");\n \n const rect = g.selectAll('rect')\n .data([null])\n .join('rect')\n .attr(\"fill\", \"#eee\")\n\n const text = g.selectAll(\"text\")\n .data([null])\n .join(\"text\")\n .call(text => text\n .selectAll(\"tspan\")\n .data((value + \"\").split(/\\n/))\n .join(\"tspan\")\n .attr(\"x\", 0)\n .attr(\"y\", (d,i) => `${i * 1.1}em`) // line spacing\n .style(\"font-weight\", (_,i) => i ? null : \"bold\") // bolds title\n .text(d => d));\n\n const {x, y, width: w, height: h} = text.node().getBBox();\n\n text.attr(\"transform\", `translate(${-w/2},${y})`);\n rect.attr('x', -w/2-5)\n .attr('y', 2*y-5)\n .attr('width', w+10)\n .attr('height', h+10)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3610,"value":"function movingAverage(data, column, N) {\n let array = data.map(d => ({'key': d.date, 'value': d[column]}))\n return array.map((row, idx, total) => {\n const startIdx = Math.max(0, idx-N+1)\n const endIdx = idx\n const movingWindow = total.slice(startIdx, endIdx+1)\n const sum = movingWindow.reduce((a,b) => a + b.value, 0)\n return {\n key: d3.timeHour.offset(row.key, 12),\n avg: sum / movingWindow.length,\n };\n });\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":2671,"value":"arc = d3.arc().innerRadius(radius * .4).outerRadius(radius * .99)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2669,"value":"pie = d3.pie()\n .value(d => d.value)\n .sort(null)\n .padAngle(0.005)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1667,"value":"growthRate = (doublingTime, refDate) => {\n let rows = daily.filter(d => d.date >= refDate)\n return rows.map(d => {\n const t = d3.timeDay.count(refDate, d.date)\n return {'date': d.date, 'value': Math.pow(2,1/doublingTime)-1}\n })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3458,"value":"expGrowth = (doublingTime, refDate, column) => {\n let data = daily.filter(d => d.date >= refDate)\n let maxDate = d3.max(data, d => d.date)\n let days = d3.timeDay.range(refDate, d3.timeSecond.offset(maxDate))\n let x0 = data[0][column]\n let expGrowth = [{'date': data[0]['date'], 'value': x0}]\n for (let day of days.slice(1)) {\n let t = d3.timeDay.count(refDate, day)\n expGrowth.push({'date': day, 'value': Math.round(x0*(Math.pow(2,t/doublingTime)))})\n }\n return expGrowth\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1075,"value":"choropleth.update(radio1)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1947,"value":"caseGrowthChart.update(radio2)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2273,"value":"ageRateChart.updateAgeRate(ageRadio)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2360,"value":"raceRateChart.updateRaceRate(raceRadio)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2504,"value":"dailyChart.updateDaily(dailyRadio)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2788,"value":"genderChart.updateGender(genderRadio)","pinned":true,"hidden":false,"mode":"ojs"},{"id":2885,"value":"ethnicityChart.update(genderRadio)","pinned":true,"hidden":false,"mode":"ojs"},{"id":3491,"value":"deathGrowthChart.update(radio3)","pinned":true,"hidden":false,"mode":"ojs"},{"id":29,"value":"colorScale = d3.scaleThreshold([1,10,100,1000,10000], d3.schemePuBu[6])","pinned":false,"hidden":false,"mode":"ojs"},{"id":1106,"value":"colorScaleRCase = d3.scaleThreshold([2000,4000,6000,8000,10000], d3.schemeOranges[6])","pinned":false,"hidden":false,"mode":"ojs"},{"id":3799,"value":"colorScaleRDeath = d3.scaleThreshold([10,20,50,100,200], d3.schemeOranges[6])","pinned":false,"hidden":false,"mode":"ojs"},{"id":4731,"value":"colorScaleHotSpot = {\n let scale = d3.schemeRdYlBu[8].reverse().slice(2,7)\n return d3.scaleThreshold([-0.1,0.1,0.25,0.5], scale).unknown('#eee')\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2326,"value":"raceColor = d3.scaleOrdinal()\n .domain(raceSeries.map(d => d.key))\n .range(d3.schemePiYG[raceSeries.length])","pinned":false,"hidden":false,"mode":"ojs"},{"id":4616,"value":"statusColor = d3.scaleOrdinal()\n .domain(statusSeries.map(d => d.key))\n .range(d3.schemePuOr[statusSeries.length])","pinned":false,"hidden":false,"mode":"ojs"},{"id":3964,"value":"countyColor = d3.scaleOrdinal()\n .domain(topCountySeries.map(d => d.key))\n .range(d3.schemeSet2.slice(0,topCountySeries.length))\n .unknown(\"#ccc\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":444,"value":"ageColor = d3.scaleOrdinal()\n .domain(ageSeries.map(d => d.key))\n .range(d3.schemeSpectral[ageSeries.length])\n .unknown(\"#ccc\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2676,"value":"genderColor = d3.schemePaired.slice(0,3)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2903,"value":"ethnicityColor = d3.schemePaired.slice(6,9)","pinned":false,"hidden":false,"mode":"ojs"},{"id":27,"value":"path = d3.geoPath().projection(projection)","pinned":false,"hidden":false,"mode":"ojs"},{"id":334,"value":"parseTime = d3.timeParse('%Y-%m-%d')","pinned":false,"hidden":false,"mode":"ojs"},{"id":629,"value":"fmtPct = d3.format('.1%')","pinned":false,"hidden":false,"mode":"ojs"},{"id":4283,"value":"numFmt = d3.format(',.0f')","pinned":false,"hidden":false,"mode":"ojs"},{"id":4859,"value":"dateFmt = d3.timeFormat('%b %e')","pinned":false,"hidden":false,"mode":"ojs"},{"id":255,"value":"type = d => {\n d.Date = parseTime(d.Date)\n d.Cases = +d.Cases\n d.Deaths = +d.Deaths || 0\n return d\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":91,"value":"projection = d3.geoMercator().fitSize([400, 400], geojson) // geoAlbersUsa","pinned":false,"hidden":false,"mode":"ojs"},{"id":935,"value":"md`## Libraries`","pinned":false,"hidden":false,"mode":"ojs"},{"id":12,"value":"d3 = require(\"d3@5\", \"d3-array@^2.2\", \"d3-dsv@1\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"import {legend, swatches} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1525,"value":"import {radio, slider} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":4185,"value":"import {Scrubber} from \"@mbostock/scrubber\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W42","stdlib":"1","titling":"auto"}