30:T69d,phaseDiv = { let theDots = JSON.parse(JSON.stringify(phaseCheckPlotData)).map(function(x) { let y = JSON.parse(JSON.stringify(x)); y.x = y.x.slice(-60) y.y = y.y.slice(-60) y.mode = 'markers' return(y) }) let regressionLines = JSON.parse(JSON.stringify(theDots)).map(function(x) { let y = JSON.parse(JSON.stringify(x)); y.x = y.x.slice(-14) y.y = y.y.slice(-14) let data = [] y.y.forEach(function (value, i) { data[i] = [i,Math.log10(value)] }) let fit = regression.linear(data) y.y.forEach(function (value, i) { y.y[i] = Math.pow(10,fit.predict(i)[1]) }) y.mode = 'lines' if(fit.equation[0] <= -(bottomFilter/10)){ y.line = {color:'rgba(0, 255, 0,0.5)',width:3} } else if(fit.equation[0] >= (topFilter/10)) { y.line = {color:'rgba(150, 0, 0,0.5)',width:3} } else { if (checkStates.includes(y.name)){ y.line = {color:'rgba(50, 50, 50,0.5)',width:3} } else { theDots = theDots.filter(x=>x.name!=y.name) y = 'delete' } } return(y) }) regressionLines = regressionLines.filter(x=>x!="delete") let theData = theDots.concat(regressionLines) theData.sort((a,b) => { if (a.name === b.name) return 0; return a.name < b.name ? -1 : 1 }); console.log(theData) var layout = { width:"100%", height:800, grid: {rows: 1, columns: 1, pattern: 'independent'}, yaxis: { domain: [0.2, 1], anchor: 'x1', title: 'New cases per day', type: 'log' }, xaxis: { title: 'Date', } }; const div = DOM.element('div1') Plotly.newPlot(div, theData,layout); return div } 31:Tc1c,faveDiv = { var theData = combinedBetterData.filter(x => [ "Italy", "Brazil", "US", "Russia","Sweden","India", ].includes(x["Country/Region"])) var universalScatterData = theData.map(x=>covidToTraceScatter(x,'new','calculatedActive21')) var dotData = JSON.parse(JSON.stringify(universalScatterData)) dotData = dotData.map(function(x) { x.x = [x.x[x.x.length-1],x.x[x.x.length-1]] x.y = [x.y[x.y.length-1], Math.round(x.y[x.y.length-dayShift2+1]/3+x.y[x.y.length-dayShift2]/3+x.y[x.y.length-dayShift2-1]/3)] x.mode = "scatter" x.marker = { size: 5, color: 'gray' }, x.line = { width: 2, dash: 'dot', color: 'gray' } x.showlegend = false return x }) universalScatterData.push(...dotData) theData = combinedBetterData.filter(x=>x.cases.reduce(( acc, cur ) => Math.max( acc, cur ),-Infinity)>5000) var rScatterData = theData.map(x=>covidToTraceScatter(x,'newR','active')) var tmpScat = { y: rScatterData.map(x=>x.y).reduce(function(prev, curr) {return [...prev,...curr]}), x: rScatterData.map(x=>x.x).reduce(function(prev, curr) {return [...prev,...curr]}), mode: 'markers', name: 'resolved cases', marker: { color: 'rgb(100,255,100)', size: 5, }, } //universalScatterData.unshift(tmpScat) var rates = [.5,.25,.15,.08,0.04,0] var colorVec = [[255,220,220],[247,227,220],[240,240,220],[220,255,220],[200,255,200]] const mn1 = Math.max(...(combinedBetterData.filter(x=>["US"].includes(x["Country/Region"]))[0].cases))*1.1 const mn2 = Math.max(...(combinedBetterData.filter(x=>["US"].includes(x["Country/Region"]))[0].new))*1.1 for(var i = 0;i<(rates.length-1);i++){ const xval = Math.min(mn1,mn2/rates[i]) const xval2 = Math.min(mn1,mn2/rates[i+1]) var trace = { y: [0,xval*rates[i],xval*rates[i],xval2*rates[i+1],0], x: [0,xval,xval2,xval2,0], mode: 'none', fill: 'toself', name: rates[i]*100+'-'+rates[i+1]*100+'% daily increase', fillcolor: 'rgb('+colorVec[i][0]+','+colorVec[i][1]+','+colorVec[i][2]+')', } universalScatterData.unshift(trace) } var layout = { width:"100%", height:600, grid: {rows: 1, columns: 1, pattern: 'independent'}, yaxis: { domain: [0.2, 1], anchor: 'x1', title: 'New cases today', range: [.8,Math.log10(mn2)], type: 'log', }, title: 'New cases as a function of active cases', xaxis: {title: 'Active cases (sum of new cases over 21 days)', type: 'log', range: [2.8,Math.log10(mn1)], }, hovermode:'closest', /* updatemenus: [{ y: 1, yanchor: 'top', buttons: [{ method: 'relayout', args: [{'yaxis.type':'linear','xaxis.type':'linear'}], label: 'linear' },{ method: 'relayout', args: [{'yaxis.type':'log','xaxis.type':'log'}], label: 'log' }] }], */ } const div = DOM.element('div1') Plotly.newPlot(div, universalScatterData,layout); return div } 32:Ta44,faveDiv2 = { // show states and large counties //var theData = [...combinedStateData,...combinedBigCountyData] var theData = [...combinedStateData] // filter selctions theData = theData.filter(x=>stateSelect.includes( x["Country/Region"]) ) // make a trace for new vs active var universalScatterData = theData.map(x=>covidToTraceScatter(x,'new','calculatedActive21')) // make a trace for current vs 7 days ago var dotData = JSON.parse(JSON.stringify(universalScatterData)) dotData = dotData.map(function(x) { x.x = [x.x[x.x.length-1]]//,x.x[x.x.length-1]] x.y = [x.y[x.y.length-1]]//,Math.round(x.y[x.y.length-7]/4+x.y[x.y.length-8]/4+x.y[x.y.length-9]/4+x.y[x.y.length-10]/4)] x.mode = "scatter" x.marker = { size:8, }, x.line = { width: 1, dash: 'dash', } return x }) // make a trace for N day lookback trail var lineData = JSON.parse(JSON.stringify(universalScatterData)) lineData = lineData.map(function(x) { x.x = x.x.slice(x.x.length-dayLookback) x.y = x.y.slice(x.y.length-dayLookback) x.mode = "lines" x.line = { size: 10, color:'rgba(0,0,0,0.3)', } x.showlegend = false return x }) // combine the two traces universalScatterData = lineData.concat(dotData) // make the background shading const maxx = Math.max(...(universalScatterData.map(x=>Math.max(...x.x)) ) )*1.1 const maxy = Math.max(...(universalScatterData.map(x=>Math.max(...x.y)) ) )*1.1 var rates = [.5,.25,.15,.08,0.04,0] var colorVec = [[255,205,200],[242,217,200],[230,230,200],[205,255,200],[150,255,150]] for(var i = 0;i<(rates.length-1);i++){ const xval = Math.min(maxx,maxy/rates[i]) const xval2 = Math.min(maxx,maxy/rates[i+1]) var trace = { y: [0,xval*rates[i],xval*rates[i],xval2*rates[i+1],0], x: [0,xval,xval2,xval2,0], mode: 'none', fill: 'toself', name: rates[i]*100+'-'+rates[i+1]*100+'% daily increase', fillcolor: 'rgb('+colorVec[i][0]+','+colorVec[i][1]+','+colorVec[i][2]+')', } universalScatterData.unshift(trace) } // plot it var layout = { width:"100%", height:600, grid: {rows: 1, columns: 1, pattern: 'independent'}, yaxis: { domain: [0, 1], anchor: 'x1', title: 'New cases today', type:'log', }, title: 'New cases as a function of active cases', xaxis: {title: 'Cases reported in last 21 days', type:'log', }, hovermode:'closest', }; const div = DOM.element('div1') Plotly.newPlot(div, universalScatterData,layout); return div } 33:T4c2,md`#### Figure 3b a deconstructed pie chart Here is a 'pie chart' in a sense that the colored area shows the breakdown of total cases into the three possible states: **active**, **recovered**, or **dead**. Instead of plotting it as a circle, the shape is described by the number of new cases diagnosed daily over time. By pushing all of the resolved cases to the left, you can get a sense of the lag between a new diagnosis and a resolution. You can also get a sense that places like the **US** are under-reporting recoveries (${ combinedBetterData.filter(x=> ["US"].includes(x["Country/Region"]))[0].recovered.slice(-1)[0] }) compared to deaths (${ combinedBetterData.filter(x=> ["US"].includes(x["Country/Region"]))[0].deaths.slice(-1)[0] }), or else the final death toll is going to be much higher than even the 4% death rate reported by China. **Germany** has the opposite problem, reporting ${ combinedBetterData.filter(x=> ["Germany"].includes(x["Country/Region"]))[0].recovered.slice(-1)[0] } recoveries compared to ${ combinedBetterData.filter(x=> ["Germany"].includes(x["Country/Region"]))[0].deaths.slice(-1)[0]} deaths. **Brazil** looks truly bizarre, setting records in new cases and new recoveries.` 34:Tbc3,waveDiv = { var layout = { width:"100%", height:400, grid: {rows: 1, columns: 1, pattern: 'independent'}, yaxis: { domain: [0.2, 1], anchor: 'x1', title: 'Daily cases', }, title: '"Pie chart" for cases in '+radioPlaces, xaxis: { title: 'Date', }, }; let waveTrace = [] let theData = combinedBetterData.filter(x=> [radioPlaces].includes(x["Country/Region"]))[0] let totalDeaths = theData.deaths.slice(-1)[0] let totalRecovered = theData.recovered.slice(-1)[0] let totalCases = theData.cases.slice(-1)[0] let totalActive = theData.active.slice(-1)[0] let totalResolved = totalDeaths + totalRecovered let dateToStop = theData.cases.findIndex(function(x) { return x > totalResolved } ) console.log(dateToStop) var caseTrace = { y: theData.new, x: theData.dates, mode: 'none', fill: 'tozeroy', name: 'active cases', fillcolor: 'rgb(100,100,255)', } waveTrace.push(caseTrace) let endDate = theData.deaths.length-1 console.log(endDate) let projectedDeaths = Math.max(0,totalActive*deathSlider/100) let y1 = theData.new[dateToStop]*(totalDeaths/(totalResolved)) let dx = Math.round((projectedDeaths*2)/y1) let y2 = 0 if(dateToStop+dx > endDate){ dx = endDate - dateToStop y2 = ((projectedDeaths*2)/dx) - y1 } var FdeathTrace = { y: [y1,y2], x: [theData.dates[dateToStop],theData.dates[dateToStop+dx]], mode: 'none', fill: 'tozeroy', name: deathSlider+'% of active cases', fillcolor: 'rgb(150,100,150)', } waveTrace.push(FdeathTrace) var deathTrace = { y: theData.new.slice(0,dateToStop+1).map(x=>x*(totalDeaths/(totalResolved))), x: theData.dates.slice(0,dateToStop+1), mode: 'none', fill: 'tozeroy', name: 'deaths', fillcolor: 'rgb(255,100,100)', } waveTrace.push(deathTrace) console.log(deathTrace) var rTrace = { y: theData.new.slice(0,dateToStop+1), x: theData.dates.slice(0,dateToStop+1), mode: 'none', fill: 'tonexty', name: 'resolved cases', fillcolor: 'rgb(100,255,100)', } waveTrace.push(rTrace) layout.annotations = [ { x: theData.dates[dateToStop-1], y: theData.new[dateToStop-1], xref: 'x', yref: 'y', text: totalRecovered +' Recoveries', showarrow: true, arrowhead: 2, ax: -40, ay: -60 }, { x: theData.dates[dateToStop-5], y: theData.new[dateToStop-5]*(totalDeaths/(totalResolved)), xref: 'x', yref: 'y', text: totalDeaths +' Deaths', showarrow: true, arrowhead: 2, ax: -40, ay: -40 }, { x: theData.dates[theData.dates.length-2], y: theData.new[theData.dates.length-2], xref: 'x', yref: 'y', text: totalActive +' Active cases', showarrow: true, arrowhead: 2, ax: -40, ay: -60 }, ] const div = DOM.element('div1') Plotly.newPlot(div, waveTrace,layout); return div } 35:T4e5,viewof checkCountries = checkbox({ options: [ { value: "US", label: "US" }, { value: "Florida,USA", label: "FL" }, { value: "Georgia,USA", label: "GA" }, { value: "North Carolina,USA", label: "NC" }, { value: "Texas,USA", label: "TX" }, { value: "California,USA", label: "CA" }, { value: "Colorado,USA", label: "CO" }, { value: "New York,USA", label: "New York" }, // { value: "New York-Suffolk", label: "New York-Suffolk" }, // { value: "New York-Nassau", label: "New York-Nassau" }, // { value: "Georgia-Gwinnett", label: "Georgia-Gwinnett" }, // { value: "Florida-Sarasota", label: "Florida-Sarasota" }, { value: "Washington", label: "Washington" }, { value: "Brazil", label: "Brazil" }, { value: "China", label: "China" }, { value: "France", label: "France" }, { value: "Germany", label: "Germany" }, { value: "Thailand", label: "Thailand" }, { value: "Italy", label: "Italy" }, { value: "Iran", label: "Iran" }, { value: "Korea, South", label: "South Korea" }, { value: "Spain", label: "Spain" }, { value: "Sweden", label: "Sweden" }, { value: "Finland", label: "Finland" }, ], value: ["New York,USA","Italy","Florida,USA","Sweden","Brazil","US"], })36:T5b2,scatterDiv = { var layout = { width:"100%", height:600, grid: {rows: 1, columns: 1, pattern: 'independent'}, yaxis: { domain: [0.2, 1], anchor: 'x1', title: yVariable, type: yScale, }, hovermode:'closest', }; if(chartSelect=="filtered"){ layout.title = yVariable+' versus '+xVariable+', places with '+Math.round(Math.pow(10,caseFilter))+ ' cases' } else { layout.title = yVariable+' versus '+xVariable+', selected countries' } layout.xaxis = { title: xVariable, } if(!(xVariable=="dates")){ layout.xaxis.type = xScale } let theTrace = universalScatterData.slice() if(!showUnity.includes("timeseries")){ theTrace = theTrace.map(function(x){ let y = JSON.parse(JSON.stringify(x)) y.x = y.x.slice(-1) y.y = y.y.slice(-1) y.mode = "scatter" return y }) } let maxx = Math.max(...(universalScatterData.map(function(x){return Math.max(...x.x,...x.y)}))) var trace = { y: [1,1+maxx/1000,1+maxx/100,1+maxx/10,maxx], x: [1,1+maxx/1000,1+maxx/100,1+maxx/10,maxx], mode: 'line', line: {color: 'gray', width: 4, }, name: 'unity line', } if(showUnity.includes("yes")){theTrace.push(trace)} const div = DOM.element('div1') Plotly.newPlot(div, theTrace,layout); return div } 37:T64f,combinedCovidData = { let cleanCases = combineByCountry(tmpCases) let cleanDeaths = combineByCountry(tmpDeaths) let cleanRecovered = combineByCountry(tmpRecovered) let listOfCountries = getUnionOfCountries([...cleanCases,...cleanDeaths,...cleanRecovered]) let covid_summary = [] for( let i = 0; i x["Country/Region"] == thiscountry) let hit2 = cleanDeaths.findIndex(x => x["Country/Region"] == thiscountry) let hit3 = cleanRecovered.findIndex(x => x["Country/Region"] == thiscountry) let combinedObj = JSON.parse(JSON.stringify(cleanCases[1])) if(hit1>0){ combinedObj = JSON.parse(JSON.stringify(cleanCases[hit1])) }else if(hit2>0){ combinedObj = JSON.parse(JSON.stringify(cleanDeaths[hit2])) }else{ combinedObj = JSON.parse(JSON.stringify(cleanRecovered[hit3])) } delete combinedObj.values if(hit1>0){ combinedObj["cases"] = cleanCases[hit1].values.slice() } else { combinedObj["cases"] = new Array(combinedObj.dates.length).fill(0) } if(hit2>0){ combinedObj["deaths"] = cleanDeaths[hit2].values.slice() } else { combinedObj["deaths"] = new Array(combinedObj.dates.length).fill(0) } if(hit3>0){ combinedObj["recovered"] = cleanRecovered[hit3].values.slice() } else { combinedObj["recovered"] = new Array(combinedObj.dates.length).fill(0) } covid_summary.push(JSON.parse(JSON.stringify(combinedObj))) } return(covid_summary) }38:T421,NYT2array = async function(theData) { const combineNytCovid = function(tocombine){ let thisState = { "Country/Region": tocombine[0]["Country/Region"], fips: tocombine[0]["fips"], dates: tocombine.map(x=>x.date), cases: tocombine.map(x=>parseFloat(x.cases)), deaths: tocombine.map(x=>parseFloat(x.deaths)), recovered: new Array(tocombine.length).fill(0), } return thisState } let shrinking = theData.slice() let aggregated = [] while(shrinking.length>0){ // outer loop, for each county let tocombine = [shrinking.shift()] let thiscountry = tocombine[0]["Country/Region"] while(true){ // inner loop, look for each match let countries = shrinking.map(x=>x["Country/Region"]) let hit = countries.findIndex(x => x == thiscountry) if(hit==-1){ break } else { tocombine.push(shrinking.splice(hit,1)[0]) } } aggregated.push(combineNytCovid(tocombine.slice())) } return aggregated }39:Ta76,addCalculatedStats = async function(aCovidArray) { return aCovidArray.map(function(oneCountry) { oneCountry = JSON.parse(JSON.stringify(oneCountry)) // smooth our the raw data oneCountry["cases"] = smooth(oneCountry["cases"],toSmooth).map(x=>Math.round(x)) oneCountry["deaths"] = smooth(oneCountry["deaths"],toSmooth).map(x=>Math.round(x)) oneCountry["recovered"] = smooth(oneCountry["recovered"],toSmooth).map(x=>Math.round(x)) // clean up dates oneCountry.dates = oneCountry.dates.map(function(x) { let thisDay = new Date(x); let stringDay = thisDay.toLocaleDateString("en-US") stringDay = stringDay.substring(0,stringDay.length) return stringDay } ) // define active cases as the remainder after subtracting deaths and recoveries oneCountry["active"] = oneCountry["cases"].map(function (num, idx) { return num - oneCountry["recovered"][idx] - oneCountry["deaths"][idx] } ) // define new cases as the difference between today and yesterday oneCountry["new"] = [oneCountry["cases"][0]] for(let i = 1;i0.5) { tmp = NaN } oneCountry.deathRate[i]= tmp*100 } oneCountry["netChangeRate"] = [0] for(let i = 1;ix.cases.reduce(( acc, cur ) => Math.max( acc, cur ),-Infinity)>Math.pow(10,caseFilter)) if(chartSelectVar == 'selected'){ theData = theData.filter(x=> checkCountries.includes(x["Country/Region"])) } if(!USA_select.includes("countries") ){ console.log('get rid of countries') console.log(theData) let hitlist = combinedGlobalData.map( x=>x["Country/Region"] ) console.log(hitlist) theData = theData.filter(function(x) { let name = x["Country/Region"] let hit = hitlist.includes(name) console.log(hit + " = " + name) return !hit } ) console.log(theData) } if(!USA_select.includes("states") ){ console.log('get rid of states') console.log(theData) let hitlist = combinedStateData.map( x=>x["Country/Region"] ) console.log(hitlist) theData = theData.filter(function(x) { let name = x["Country/Region"] let hit = hitlist.includes(name) console.log(hit + " = " + name) return !hit } ) console.log(theData) } /* if(!USA_select.includes("counties") ){ console.log('get rid of states') console.log(theData) let hitlist = combinedBigCountyData.map( x=>x["Country/Region"] ) console.log(hitlist) theData = theData.filter(function(x) { let name = x["Country/Region"] let hit = hitlist.includes(name) console.log(hit + " = " + name) return !hit } ) console.log(theData) } */ let theTrace = theData.map(x=>covidToTraceShifted(x,dateShift=="yes",thisCaseSync,thisVariable)) return theTrace }3b:T6a9,universalScatterData = { let theData = [] if(chartSelect == 'selected'){ theData = combinedBetterData .filter(x=> checkCountries.includes(x["Country/Region"])) } else if(chartSelect == 'filtered'){ theData = combinedBetterData .filter( x=>x.cases.reduce( ( acc, cur ) => Math.max( acc, cur ),-Infinity)>Math.pow(10,caseFilter)) } if(!USA_select.includes("countries") ){ console.log('get rid of countries') console.log(theData) let hitlist = combinedGlobalData.map( x=>x["Country/Region"] ) console.log(hitlist) theData = theData.filter(function(x) { let name = x["Country/Region"] let hit = hitlist.includes(name) console.log(hit + " = " + name) return !hit } ) console.log(theData) } if(!USA_select.includes("states") ){ console.log('get rid of states') console.log(theData) let hitlist = combinedStateData.map( x=>x["Country/Region"] ) console.log(hitlist) theData = theData.filter(function(x) { let name = x["Country/Region"] let hit = hitlist.includes(name) console.log(hit + " = " + name) return !hit } ) console.log(theData) } /* if(!USA_select.includes("counties") ){ console.log('get rid of states') console.log(theData) let hitlist = combinedBigCountyData.map( x=>x["Country/Region"] ) console.log(hitlist) theData = theData.filter(function(x) { let name = x["Country/Region"] let hit = hitlist.includes(name) console.log(hit + " = " + name) return !hit } ) console.log(theData) } */ let theTrace = theData.map(x=>covidToTraceScatter(x,yVariable,xVariable)) return theTrace }3c:T4c1,timeRelationshipScatter = { let theData = [] theData = combinedBetterData.filter( x=>x.cases.reduce( ( acc, cur ) => Math.max( acc, cur ),-Infinity)>1000000) theData = theData.map(function(x) { let y = JSON.parse(JSON.stringify(x)) y.dates = x.dates.slice() y.new = x.new.slice() y.newDeaths = x.newDeaths.slice() return(x) }) let theTrace = theData.map(x=>covidToTraceScatter(x,'newDeaths','new',dayShift)) theTrace = theTrace.map(function(x){ let y = JSON.parse(JSON.stringify(x)) y.mode = 'markers' y.x = smooth(y.x) y.y = smooth(y.y) return y }) var trace = { y: [.02,2000], x: [1,100000], mode: 'line', line: { color: 'gray', width: 4, }, name: '2% unity line', } var trace2 = { y: [.1,10000], x: [1,100000], mode: 'line', line: { color: 'darkgray', width: 4, }, name: '10% unity line', } var trace3 = { y: [.5,50000], x: [1,100000], mode: 'line', line: { color: 'black', width: 4, }, name: '50% unity line', } theTrace.unshift(trace) theTrace.unshift(trace2) theTrace.unshift(trace3) return theTrace }3d:T56c,smooth = function(theArray,ammount=1) { if(ammount==0){ return theArray } let L = theArray.length // first, leave the end points intact let result = theArray.slice() // then do the inside edge cases let poi = [1,L-2] for(let i = 0; ix[1]))) let minY = Math.min(...(data.map(x=>x[1]))) let newvalue = Math.min(Math.max(minY,estimate[1]),maxY) //console.log('max: ' + maxY +' min: ' + minY +' new: ' + newvalue) result[i] = newvalue } return result }3e:[] 2e:{"title":"COVIDv2","cells":[{"id":2541,"value":"md`# COVIDv2`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4259,"value":"md`October update: disabled county level data for speed.`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":1043,"value":"md`## Some pretty plots for an ugly virus\n\nGlobal data is pulled on demand from [CSSE at Johns Hopkins University](https://github.com/CSSEGISandData/COVID-19), and state data are derived from [The New York Times](https://github.com/nytimes/covid-19-data). Check below the plot for timestamps on the last modifications from each github repo. Check the bottom of this notebook for a list of libraries used. I also recommend checking out [Jonas's page](https://observablehq.com/@episphere/corona) for a more technical discussion of this type of data. If you prefer, I have a [notebook with map data](https://observablehq.com/@rmoffitt/covid-maps) as well.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3871,"value":"md`## Gating criteria \nAccording to [the white house](https://www.whitehouse.gov/openingamerica/#criteria), states are required to have a \"downward trajectory of covid-like syndromic cases reported within a 14-day period\" before phased reopening. Which states are meeting this criteria?`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3874,"value":"viewof topFilter = slider({\n min: 0, \n max: 1,\n step: 0.01,\n value: .22,\n format: v => 'show states increasing at least '+(((Math.pow(10,v/10)-1)*100).toFixed(2))+'% per day',\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3879,"value":"viewof bottomFilter = slider({\n min: 0, \n max: 1,\n step: 0.01,\n value: 0.22,\n format: v => 'show states decreasing at least '+((Math.pow(10,v/10)-1)*100).toFixed(2)+'% per day',\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":4017,"value":"\n\nviewof checkStates = select({\n description: 'always show these locations',\n options: [...(NYTArray.map(x=>x[\"Country/Region\"]))].sort(),\n value:[],\n multiple: true,\n size:10\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3885,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":2832,"value":"viewof toSmooth = radio({\n options: [\n { label: 'Show raw data', value: 0},\n { label: 'Apply smoothing', value: 1},\n ],\n value: 1\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2474,"value":"md`### Figure 1. Are we making progress?\n#### (4/18 Will BRICS countries be the next hot spot?)\n#### (4/29 Brazil about to look worse than NY)\n#### (5/23 Brazil looks very bad, Russia and India limping along)\n#### (6/6 Sweden surpasses Italy)\n#### (7/1 US re-takes the lead from Brazil)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2147,"value":"md` Below I'm showing the number of new cases compared to the day's active total. It gives a sense of how fast the spread is-- what percent of each infected case is responsible for infecting a new person today. A place could theoretically achieve a steady-state of active infections, i.e. 'a flat curve', if the number of new cases diagnosed that day is balanced by the number of people that resolve each day. If the duration of illness is 12.5 days, 8% of cases should resolve each day at steady-state. The dashed lines show the gap between today's new cases and the number of new diagnoses from around ${dayShift2} days ago (a 3 day moving average), which presumably should be resolving soon, given that a typical positive test result is probably in a patient already showing symptoms.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3005,"value":"viewof dayShift2 = slider({\n min: 0, \n max: 15, \n step: 1, \n value: 10,\n format: v => `Compare to cases from ${v} days ago`,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2025,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":2477,"value":"md`### Figure 2. The Laboratories of Democracy\n#### (6/6 Southern states record more new cases than northern hotspots)\n#### (7/1 And it is just getting worse)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2396,"value":"md` This is the same plot, for the states & counties selected below. Transparent black tails of the comets show the recent few days for each location. `","pinned":false,"hidden":false,"mode":"ojs"},{"id":2400,"value":"viewof dayLookback = slider({\n min: 1, \n max: 60,\n step: 1,\n value: 21,\n format: v => 'show trails for '+v+' days',\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2360,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":3998,"value":"viewof stateSelect = await select({\n description: 'use ctrl to select additional locations',\n // options: [...(NYTArray.map(x=>x[\"Country/Region\"])),...(BigCountyArray.map(x=>x[\"Country/Region\"]))].sort(),\n options: [...(NYTArray.map(x=>x[\"Country/Region\"]))].sort(),\n value:[\"New York,USA\",\n \"Florida,USA\",\n \"Texas,USA\",\n \"Georgia,USA\",\n \"California,USA\",\n ],\n multiple: true,\n size:10\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3519,"value":"md`### Figure 2b \nI once had a map here, but I moved it to [a new notebook](https://observablehq.com/@rmoffitt/covid-maps)`\n\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":3582,"value":"html` $\"my$ `\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2944,"value":"md`### Figure 3 - understand the lag\nHere we want to look at how long will it take for a newly diagnosed case to contribute to deaths. The idea is by plotting the number of cases diagnosed N days ago versus the number of new deaths today, if we get the \"N\" right, they should lie along the unity line, i.e. the cases that got diagnosed N days ago are resolving today.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2980,"value":"md`#### During the beginning phase...\nNew deaths were 10% of the new cases reported a week prior.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2942,"value":"viewof dayShift = slider({\n min: -10, \n max: 40, \n step: 1, \n value: 7,\n format: v => `look at cases from ${v} days ago`,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2939,"value":"delayDiv = {\n var layout = {\n width:\"100%\",\n height:600,\n grid: {rows: 1, columns: 1, pattern: 'independent'},\n yaxis: {\n domain: [0.2, 1],\n anchor: 'x1',\n title: 'New Deaths',\n type: 'log',\n },\n hovermode:'closest',\n\n };\n\n layout.title = 'Places with 10k cases'\n\n layout.xaxis = {\n title: 'New cases from N days before',\n type: 'log',\n }\n\n const div = DOM.element('div1')\n Plotly.newPlot(div, timeRelationshipScatter,layout);\n return div\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":3052,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":3096,"value":"viewof radioPlaces = radio({\n options: [\n { value: \"US\", label: \"US\" },\n { value: \"China\", label: \"China\" },\n { value: \"Italy\", label: \"Italy\" },\n { value: \"Brazil\", label: \"Brazil\" },\n { value: \"Korea, South\", label: \"South Korea\" },\n { value: \"Spain\", label: \"Spain\" },\n { value: \"Germany\", label: \"Germany\" },\n { value: \"Sweden\", label: \"Sweden\" },\n ],\n value: \"US\",\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3149,"value":"viewof deathSlider = slider({\n min: .5, \n max: 15, \n value: 4,\n format: v => `Project death rate for active cases at ${v}%`,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3035,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":2480,"value":"md`### Figure 4 & 5 - make your own plots`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1190,"value":"viewof whichVariable = radio({\n title: \"What to plot\",\n options: [{ label: 'Active cases (21 day)', value: \"calculatedActive21\"},\n { label: 'Total cases', value: \"cases\"},\n { label: 'Deaths', value: \"deaths\"},\n { label: 'Recovered', value: \"recovered\"},\n { label: 'New cases', value: \"new\"},\n { label: 'New deaths', value: \"newDeaths\"},\n { label: 'Total Deaths/Cases', value: \"deathRate\"},\n { label: '% daily change', value: \"netChangeRate\"},\n ],\n value: \"new\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1208,"value":"viewof whichScale = radio({\n title: \"Scale\",\n options: [\"linear\",\"log\"],\n value: \"log\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1319,"value":"viewof dateShift = radio({\n title: 'Synchronize trajectories, or show real dates?',\n options: [\n { label: 'Dates', value: \"no\" },\n { label: 'Synchronize', value: \"yes\" },\n ],\n value: \"no\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1304,"value":"viewof caseSync = slider({\n min: 1, \n max: 5, \n value: 3,\n format: v => `Synchronize countries at ${Math.round(Math.pow(10,v))} `+whichVariable,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1408,"value":"viewof chartSelect = radio({\n title: 'Which places should we look at?',\n options: [\n { label: 'Only these selections', value: 'selected' },\n { label: 'Just filter by number of cases', value: 'filtered' },\n\n ],\n value: 'selected'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2574,"value":"viewof USA_select = checkbox({\n options: [\n { label: 'Countries', value: 'countries' },\n { label: 'US States', value: 'states' },\n // { label: 'US Counties', value: 'counties' },\n ],\n value: ['countries','states','counties']\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1300,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":1392,"value":"viewof caseFilter = slider({\n min: 0, \n max: 6, \n step: 0.1, \n value: 3,\n format: v => `Include places with a minimum of ${Math.round(Math.pow(10,v))} cases`,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1278,"value":"shownDiv = {\n var layout = {\n width:\"100%\",\n height:600,\n grid: {rows: 1, columns: 1, pattern: 'independent'},\n yaxis: {\n domain: [0.2, 1],\n anchor: 'x1',\n title: whichVariable,\n type: whichScale,\n },\n };\n\n if(chartSelect==\"filtered\"){\n layout.title = whichVariable+', places with '+Math.round(Math.pow(10,caseFilter))+\n ' cases'\n } else {\n layout.title = whichVariable+', selected places'\n }\n\n if(dateShift==\"yes\"){\n let maxx = universalPlotData.map(x=>x.x).reduce(\n ( acc, cur ) => acc.concat(cur),[]).reduce(\n ( acc, cur ) => Math.max( acc, cur ),-Infinity)\n layout.xaxis = {\n range: [-5, maxx],\n title: 'Days since reaching '+Math.round(Math.pow(10,caseSync))+' '+whichVariable,\n }\n } else {\n layout.xaxis = {\n title: 'Date',\n }\n }\n const div = DOM.element('div1')\n Plotly.newPlot(div, universalPlotData,layout);\n return div\n }\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":1777,"value":"viewof xVariable = radio({\n title: \"What to plot on x\",\n options: [{ label: 'Active cases (21 day)', value: \"calculatedActive21\"},\n { label: 'Total cases', value: \"cases\"},\n { label: 'Deaths', value: \"deaths\"},\n { label: 'Recovered', value: \"recovered\"},\n { label: 'New cases', value: \"new\"},\n { label: 'Total Deaths/Cases', value: \"deathRate\"},\n { label: 'Time', value: \"dates\"}],\n value: \"cases\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2865,"value":"viewof xScale = radio({\n options: [\"linear\",\"log\"],\n value: \"log\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1780,"value":"viewof yVariable = radio({\n title: \"What to plot on y\",\n options: [{ label: 'Active cases', value: \"active\"},\n { label: 'Total cases', value: \"cases\"},\n { label: 'Deaths', value: \"deaths\"},\n { label: 'Recovered', value: \"recovered\"},\n { label: 'New cases', value: \"new\"},\n { label: 'New deaths', value: \"newDeaths\"},\n { label: 'New deaths+recoveries', value: \"newR\"},\n { label: 'Total Deaths/Cases', value: \"deathRate\"},\n { label: '% daily change', value: \"netChangeRate\"},\n \n ],\n value: \"new\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":2871,"value":"viewof yScale = radio({\n options: [\"linear\",\"log\"],\n value: \"log\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3227,"value":"viewof showUnity = checkbox({\n options: [{label:\"Show unity line\",value:\"yes\"},{label:\"Show timeseries\",value:\"timeseries\"}],\n value: [\"timeseries\"]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1773,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":2351,"value":"md`### NYT commit log:`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2348,"value":"table(modTableNYT)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2354,"value":"md`### JHU commit log:`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1397,"value":"table(modTable)","pinned":false,"hidden":false,"mode":"ojs"},{"id":25,"value":"md`# Backend`","pinned":false,"hidden":false,"mode":"ojs"},{"id":568,"value":"md`## Data pulling`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1867,"value":"md`### Raw data into array of JSON`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1157,"value":"pull_covid = async function(url) {\n let rawTxt = await (await fetch(url)).text()\n let rawArray = rawTxt.split(/\\r\\n|\\n/g).map(x=>mysplit(x))\n // trailing blank\n if((rawArray.slice(-1)[0].length==1)&isNaN(rawArray.slice(-1)[0][0])){ \n rawArray=rawArray.slice(0,-1)\n }\n let header = rawArray[0]\n rawArray = rawArray.slice(1) \n console.log(rawArray[0])\n let jsonVec = rawArray.map(function(x) {\n let m = new Object()\n for (let i = 0; i < 4; i++) { m[header[i]] = x[i] }\n m[\"values\"] = x.slice(4).map(x=>parseFloat(x))\n m[\"dates\"] = header.slice(4)\n return(m)\n })\n return(jsonVec)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1847,"value":" tmpCases = await pull_covid('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv')","pinned":false,"hidden":false,"mode":"ojs"},{"id":1858,"value":"tmpDeaths = await pull_covid('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv')","pinned":false,"hidden":false,"mode":"ojs"},{"id":1861,"value":"tmpRecovered = await pull_covid('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv')","pinned":false,"hidden":false,"mode":"ojs"},{"id":2241,"value":"pullNYTcovid = async function(url) {\n let rawTxt = await (await fetch(url)).text()\n let rawArray = rawTxt.split(/\\r\\n|\\n/g).map(x=>mysplit(x))\n // trailing blank\n if((rawArray.slice(-1)[0].length==1)&isNaN(rawArray.slice(-1)[0][0])){ \n rawArray=rawArray.slice(0,-1)\n }\n let header = rawArray[0]\n console.log(rawArray.slice(0,2))\n rawArray = rawArray.slice(1) \n let jsonVec = rawArray.map(function(x) {\n let m = new Object()\n for (let i = 0; i < header.length; i++) {\n m[header[i]] = x[i] \n }\n return(m)\n })\n return(jsonVec)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2242,"value":"NYTdata = await pullNYTcovid(\"https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-states.csv\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2549,"value":"// NYTdataCounty = await pullNYTcovid(\"https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":1990,"value":"md`### Combine by country and merge cases, deaths, recovered`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1877,"value":"combineByCountry = function(covidObject) {\n let shrinking = covidObject.slice()\n let aggregated = []\n while(shrinking.length>0){\n // outer loop, for each county\n let tocombine = [shrinking.shift()]\n let thiscountry = tocombine[0][\"Country/Region\"]\n while(true){\n // inner loop, look for each match\n let countries = shrinking.map(x=>x[\"Country/Region\"])\n let hit = countries.findIndex(x => x == thiscountry)\n if(hit==-1){\n break\n } else {\n tocombine.push(shrinking.splice(hit,1)[0])\n }\n }\n aggregated.push(combineSimpleCovid(tocombine.slice()))\n }\n return aggregated\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1882,"value":"// a function to combine covid objects by summing thier daily values\ncombineSimpleCovid = function(theInput) { \n let _combine = function(theInnerInput) {\n if(theInnerInput.length == 1){\n return(theInnerInput[0])\n } \n let popped1 = theInnerInput.pop()\n let popped2 = theInnerInput.pop()\n let combinedObj = JSON.parse(JSON.stringify(popped1))\n combinedObj[\"Province/State\"] = \"Combined\"\n \n let tmp1 = popped1[\"values\"].slice()\n let tmp2 = popped2[\"values\"].slice()\n combinedObj[\"values\"] = tmp1.map(function (num, idx) {return num + tmp2[idx]} )\n \n theInnerInput.push(combinedObj)\n return(_combine(theInnerInput))\n }\n return(_combine(theInput))\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1916,"value":"getUnionOfCountries = function(x){\n let theList = [...new Set(x.map(x=>x[\"Country/Region\"]))]\n theList = theList.filter(function(x) {return !(typeof x == \"undefined\")})\n theList = theList.sort()\n return theList\n }","pinned":false,"hidden":false,"mode":"ojs"},{"id":932,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":2269,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":2273,"value":"NYTArray = {\n let theData = NYTdata\n theData = theData.map(function(x){\n let y = JSON.parse(JSON.stringify(x))\n y[\"Country/Region\"] = y.state +\",USA\"\n return y\n }) \n return await NYT2array(theData)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4242,"value":"viewof internalCountyCaseCutoff = slider({\n min: 2000, \n max: 10000,\n step: 500,\n value: 7500,\n title: \"Minimum case level to extract county data\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":3251,"value":"/* BigCountyArray = {\n let theData = NYTdataCounty\n theData = theData.map(function(x) {\n let y = JSON.parse(JSON.stringify(x))\n y[\"Country/Region\"] = y.state+'-'+y.county \n return y\n })\n \n let datesToKeep = new Set(theData.map(x=>x[\"date\"]))\n datesToKeep = [...datesToKeep].sort().slice(-1)\n let recentData = theData.filter(x=>datesToKeep.includes(x[\"date\"]))\n \n let placesToKeep = new Set(recentData.filter(x=>x.cases>internalCountyCaseCutoff).map(x=>x[\"Country/Region\"]))\n placesToKeep = [...placesToKeep]\n theData = theData.filter(x=>placesToKeep.includes(x[\"Country/Region\"]))\n \n theData = NYT2array(theData)\n return await theData\n}\n*/","pinned":false,"hidden":false,"mode":"ojs"},{"id":1992,"value":"md`### Add calculated stats: new, active, rates`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3978,"value":"viewof internalDeathSlider = slider({\n min: 0, \n max: 12, \n value: 2.5,\n format: v => `Project death rate for active cases at ${v}%`,\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1965,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":2290,"value":"combinedGlobalData = await addCalculatedStats(combinedCovidData)","pinned":false,"hidden":false,"mode":"ojs"},{"id":2281,"value":"combinedStateData = await addCalculatedStats(NYTArray) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":3293,"value":"// combinedBigCountyData = await addCalculatedStats(BigCountyArray) ","pinned":false,"hidden":false,"mode":"ojs"},{"id":2292,"value":"// combinedBetterData = await combinedGlobalData.concat(combinedStateData).concat(combinedBigCountyData)\ncombinedBetterData = await combinedGlobalData.concat(combinedStateData)","pinned":false,"hidden":false,"mode":"ojs"},{"id":570,"value":"md`## Prepare for plotting`","pinned":false,"hidden":false,"mode":"ojs"},{"id":364,"value":"covidToTraceShifted = function(covid,isShifted,thisCaseSync,thisVariable) {\n \n let trace = new Object()\n trace.y = covid[thisVariable]\n if(isShifted){\n let dayshift = trace.y.findIndex(x=>x>Math.pow(10,thisCaseSync))\n if(dayshift==-1){\n dayshift = trace.y.length\n } else if (dayshift <= 1){\n } else {\n dayshift = dayshift - 1 + (Math.pow(10,thisCaseSync) - trace.y[dayshift-1])/(trace.y[dayshift]-trace.y[dayshift-1])\n }\n trace.x = Array.from(trace.y.keys()).map(x=>x-dayshift)\n } else {\n trace.x = Array.from(covid[\"dates\"])\n }\n trace.mode = 'lines'\n trace.name = covid[\"Country/Region\"]\n if(covid[\"Country/Region\"]==\"US\"){\n trace.line = {\n width: 4,\n color: 'rgb(0, 0, 255S)'\n }\n\n }\n return trace\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1702,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":1385,"value":"universalPlotData = makePlotFromArray(combinedBetterData,caseFilter,caseSync,whichVariable,USA_select,chartSelect)","pinned":false,"hidden":false,"mode":"ojs"},{"id":3691,"value":"phaseCheckPlotData = makePlotFromArray(combinedStateData,0,0,\"new\",[\"states\"],\"filtered\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":1529,"value":"covidToTraceScatter = function(covid,yVariable,xVariable,dayShift=0) {\n let trace = new Object()\n if(dayShift<0){\n trace.y = covid[yVariable].slice(0,dayShift)\n trace.x = covid[xVariable].slice(-dayShift)\n }\n if(dayShift==0){\n trace.y = covid[yVariable]\n trace.x = covid[xVariable]\n }\n if(dayShift>0){\n trace.y = covid[yVariable].slice(dayShift)\n trace.x = covid[xVariable].slice(0,-dayShift)\n }\n trace.mode = 'lines'\n trace.name = covid[\"Country/Region\"]\n if(covid[\"Country/Region\"]==\"US\"){\n trace.line = {\n width: 4,\n color: 'rgb(0, 0, 255S)'\n }\n }\n let minL = Math.min(trace.x.length,trace.y.length)\n trace.y = trace.y.slice(0,minL)\n trace.x = trace.x.slice(0,minL)\n \n return trace\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1520,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs"},{"id":2886,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs"},{"id":3219,"value":"selectionList = {\n let maxCases = NYTArray.map(function(x){return {name: x[\"Country/Region\"],\n max: Math.max(...(x.cases)),}\n })\n maxCases.keys\n return maxCases\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":2019,"value":"md`## String parsing`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2010,"value":"mysplit = function(x) {\n if(x[0]==\",\"){\n x = \" \" + x\n }\nlet odd = x.split(/,\"|\",|\"/)\nlet bigx = []\nfor(let i = 0; imysplit(x))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2633,"value":"md`## Smoothing functions`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2636,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs"},{"id":2643,"value":"smoothDiv = {\n \n let x = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]\n let y = [0,0,1,0,0,0,5,9,4,17,17,17,17,19,19,19,19,19,10,0,0,0,0]\n let yhat = smooth(y,toSmooth)\n let smoothPlotData = []\n \n let trace = new Object()\n trace.y = y\n trace.x = x\n trace.mode = 'markers'\n trace.name = 'original'\n smoothPlotData.push(trace)\n \n trace = new Object()\n trace.y = yhat\n trace.x = x\n trace.mode = 'lines'\n trace.name = 'smooth'\n smoothPlotData.push(trace)\n \n const div = DOM.element('div1')\n Plotly.newPlot(div, smoothPlotData);\n return div\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":11,"value":"md`# Libraries\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1083,"value":"md`## User inputs\nhttps://observablehq.com/@jashkenas/inputs`","pinned":false,"hidden":false,"mode":"ojs"},{"id":951,"value":"import {slider} from \"@jashkenas/inputs\"\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":1215,"value":"import {checkbox} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1270,"value":"import {radio} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":3172,"value":"import {select} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1079,"value":"md`## Pretty table and git data\nhttps://observablehq.com/@tmcw/tables`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1076,"value":"modTable = {\n let result = await (await fetch(\"https://api.github.com/repos/CSSEGISandData/COVID-19/commits?path=csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv\") ).json()\n let myTable = []\n for(let i = 0; i<3 ; i++){\n let thisresult = result[i]\n \n let mydate = thisresult.commit.committer.date\n let myActualDate = new Date(mydate)\n let prettyDate = myActualDate.toString()\n \n let out = new Object()\n out.timestamp = prettyDate\n out.comment = thisresult.commit.message\n myTable.push(out)\n }\n return myTable\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2337,"value":"modTableNYT = {\n let result = await (await fetch(\"https://api.github.com/repos/nytimes/covid-19-data/commits?path=us-states.csv\") ).json()\n let myTable = []\n for(let i = 0; i<3 ; i++){\n let thisresult = result[i]\n \n let mydate = thisresult.commit.committer.date\n let myActualDate = new Date(mydate)\n let prettyDate = myActualDate.toString()\n \n let out = new Object()\n out.timestamp = prettyDate\n out.comment = thisresult.commit.message\n myTable.push(out)\n }\n return myTable\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1066,"value":"import {table} from \"@tmcw/tables@513\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1081,"value":"md`## Plotly!\nhttps://cdn.plot.ly/plotly-latest.min.js`","pinned":false,"hidden":false,"mode":"ojs"},{"id":37,"value":"Plotly = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2666,"value":"md`## Regression!\nhttps://github.com/Tom-Alexander/regression-js`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2748,"value":"regression = require('https://unpkg.com/regression@2.0.1/dist/regression.js')","pinned":false,"hidden":false,"mode":"ojs"},{"id":2536,"value":"md`## Editors note\nFingers crossed that it won't end up like my [old notebook](https://observablehq.com/@rmoffitt/covid)`","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W3e","stdlib":"1","titling":"auto"}