Principal Web Developer at Freedom of the Press Foundation
Published
Edited
Feb 2, 2021
6 stars
Andy's Walgreens COVID-19 Tracker TrackerBelgium Vaccination Tracker - Progress of the vaccination campaignVaccination against covid-19 in France500,000 COVID-19 DeathsCovid-19 vaccinations: BubblesTime Spiral with a COVID DemoCOVID MasksGrid Cartogram component with live COVID demos (plus a MapEditor)The US COVID SyringeCOVID-19 DKCOVID-19 World Community Mobility Report by GoogleCOVID 19Chicago COVID ZIP SparklinesThe COVID Syringeభారతదేశంలో కోవిడ్-19SVG DataGrid with many features and a live COVID Dashboard demoThe spread of Covid-19 in New MexicoHeatmap of COVID-19 Confirmed Cases by Age over Time in JapanThe CoViD-19 ReportCovid19 WorldwideChoropleth map about Covid19 in FranceWell ordered coronavirus heatmaps for US and the WorldCOVID-19 Racial/Ethnic Mortality AnalysisProPublica's COVID Arrow MapClustering students to slow virus spread inside schoolsCOVID-19 in the USAWho Is Wearing Masks in the U.S.Covid-19 Viz RoundupCoronavirus StatsThe Covid-19 Crisis' Impact on the Number of US Flight PassengersCOVID-19 Daily New CasesCOVID-19 CasesCOVID–19 Bubble Chart with D3 RenderCoronavirus Deaths by Race / EthnicityHow many SARS-CoV-2 tests are we running in the U.S.?COVID-19 Onset vs. ConfirmationPeaks in confirmed daily deaths due to COVID-19 so farCOVID-19 in the U.S.Recreating John Burn-Murdoch’s Coronavirus trackerTracking COVID-19 Cases in VietnamCOVID-19 in NYC by Zip Code & IncomeVisualizing the Network Meta-Analysis of Covid-19 Studiesxkcd COVID-19 spread sketchCOVID-19's deaths in EuropeCovid-19 (corona virus) deaths per 1,000,000 peopleCOVID-19 Bubble map or spike map? (Twitter debate)A Timeline of Shelter-in-PlaceWhere’s that $2 trillion going?Estimating SARS-COV-2 infectionsCODAVIM - CountySARS-CoV-2 Epi CurveCOVID-19 Curves (U.S.)COVID-19 Cases by CountyCOVID-19 world growth rateA graphical experiment of exponential spreadCOVID-19 by US countyCOVID-19 Confirmed vs. New cases"Live" Logistic Coronavirus Death CounterInfografiche: COVID-19 in ItaliaCoronavirus (COVID-19) GlobeBar Chart Race, COVID-19 outbreak Worldwide to 24th March 2020US Coronavirus testing by statesUnited States Coronavirus Daily Cases Map (COVID-19)COVID-19 Numbers by State, Side by SideRecreating NYT U.S. Cases MapCOVID-19 in Washington stateCOVID-19 outbreak in maps and chartsCOVID-19 Spreading trendsRestaurants during COVID-19 social distancingCOVID-19 Countries Trajectories in 3DStates that aren't reporting aspects of their COVID-19 testing processNextstrain Prototyping - Issue 817Reviewing COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxivCoronavirus worldwide evolutionCovid-19 New Cases PunchcardCovid-19 cases per district in Germany.COVID-19 Cases, Deaths, and Recoveries (Select Country)Quarantine NowEmissions in WuhanCOVID-19(nCOV-2019) Outbreak in S.KoreaMovement of population between provinces in 2019-nCoVComparing COVID-19 GrowthCovid-19 derived chartCoronavirus Trends (COVID-19)Netherlands Coronavirus Daily Cases Map (COVID-19)Map and timeline of Corona outbreakSARS-CoV-2 Phylogenetic TreeCoronavirus data (covid-19)Visualizing the Logic of Exponential Viral SpreadItaly Coronavirus Daily Cases Map (COVID-19)COVID-19 Fatality Rate
Massachusetts Coronavirus Cases by Town
Also listed in…
Coronavirus
townData = aq.fromCSV(await (await fetch(CORSPROXY + TOWN_CASES_CSV)).text())
annotatedTownData = townData
// Add town pop data
.join(massPopulations, ['Town', 'Town'], [aq.all(), ['Population']])
// Annotate rows with case counts suppressed (MA does this for small towns for privacy reasons)
.derive({ 'Cases Hidden': d => d['Total Cases'] === '<5' ? true : false })
// Calculate change from previous week per town using a window function
// If case counts are suppressed calculate new cases to be 0
.groupby('Town')
.derive({
'New Cases': aq.rolling(
d => d['Cases Hidden'] ? 0 : d['Total Cases'] - op.lag(d['Total Cases'], 1)
),
'New Tests': aq.rolling(
d => op.equal(op.lag(d['Total Tests'], 1, 0), null) ? null : d['Total Tests'] - op.lag(d['Total Tests'], 1, 0)
),
'Cases Suppressed': d => op.equal(d['Total Cases'], '<5')
})
.derive({
'Increased By': aq.rolling(
d => d['New Cases'] && op.lag(d['New Cases'], 1) ?
(d['New Cases'] - op.lag(d['New Cases'], 1, 0)) / op.lag(d['New Cases'], 1) :
null
),
'New Cases Per Capita': d => d['New Cases'] / d['Population'],
'Positivity': d => d['New Cases'] && d['New Tests'] ? d['New Cases'] / d['New Tests'] : null
})
.ungroup()
mapSize = ({ width: 800, height: 500 })
// We use epsilon to guarantee that thresholds are inclusive on the top end
perCapitaColorScale = d3.scaleThreshold()
.domain([
0 + Number.EPSILON,
0.0001 + Number.EPSILON,
0.00025 + Number.EPSILON,
0.0005 + Number.EPSILON,
0.001 + Number.EPSILON,
0.002 + Number.EPSILON,
])
.range(['#CED', '#BDC', '#FD4', '#FA0', '#F44', '#900', '#400'])
noDataPattern = textures.circles()
.thicker()
.complement()
.size(10)
.background(perCapitaColorScale(0))
.fill('#FFF')
barChart = data => {
const dim = {
width: 300,
height: 150,
top: 5,
left: 40,
bottom: 40,
right: 20,
}
const casesFieldName = 'New Cases Per Capita' // 'New Cases'
const timeScale = d3.scaleTime()
.domain([
d3.min(data, d => d.Date),
d3.max(data, d => d.Date)
])
.range([dim.left, dim.width - dim.right])
const caseScale = d3.scaleLinear()
.domain([
0,
Math.max(0.003, d3.max(data, d => d[casesFieldName]))
])
.range([dim.height - dim.bottom, dim.top])
const leftAxis = d3.axisLeft(caseScale)
.ticks(5)
.tickFormat(d => d3.format('d')(d * 100000))
const bottomAxis = d3.axisBottom(timeScale)
.tickFormat(d3.timeFormat('%b'))
const chart = d3.select(svg`<svg viewbox="0 0 ${dim.width} ${dim.height}"/>`)
chart.append('g')
.attr('transform', `translate(${dim.left}, 0)`)
.call(leftAxis)
chart.append('g')
.attr('transform', `translate(0, ${dim.height - dim.bottom})`)
.call(bottomAxis)
chart.append('g')
.selectAll('rect')
.data(data.filter(d => !isNaN(d[casesFieldName])))
.join('rect')
.attr('x', d => timeScale(d3.timeWeek.offset(d.Date, -1)) + 1)
.attr('y', d => caseScale(d[casesFieldName]))
.attr('width', d => timeScale(d.Date) - timeScale(d3.timeWeek.offset(d.Date, -1)) - 2)
.attr('height', d => dim.height - dim.bottom - caseScale(d[casesFieldName]))
.attr('fill', d => perCapitaColorScale(d[casesFieldName]))
const latest2 = data.slice(-2)
chart.append('line')
.attr('x1', )
return chart.node()
}
casesTable = data => html`
<table style="margin-top: 0">
<thead>
<tr>
<th>Week Ending On</th>
<th>7-Day Cases</th>
<th>New Cases per 100k</th>
</tr>
</thead>
<tbody>
${data.slice(-5).reverse().map(d => html`
<tr>
<td>${d3.utcFormat('%x')(d.Date, -1)}</td>
<td>${d['New Cases']}</td>
<td>${d3.format('d')(d['New Cases Per Capita'] * 100000)}</td>
</tr>
`)}
</tbody>
</table>
`
townDetails = recentDatum => html`
<table>
<tr>
<th>Population</th>
<td style="text-align: right; font-variant-numeric: tabular-nums;">
${d3.format(',d')(recentDatum.Population)}
</td>
</tr>
<tr>
<th>Total Cases</th>
<td style="text-align: right; font-variant-numeric: tabular-nums;">
${d3.format(',d')(recentDatum['Total Cases'])}
</td>
</tr>
<tr>
<th>Total Tests</th>
<td style="text-align: right; font-variant-numeric: tabular-nums;">
${d3.format(',d')(recentDatum['Total Tests'])}
</td>
</tr>
</table>
`
viewof selectedTown = new View(null)
mapUpdater = {
const data = annotatedTownData
.params({ selectedDate })
.filter((d, $) => op.equal(d.Date, $.selectedDate))
.select('Town', 'New Cases Per Capita', 'Cases Hidden')
.objects()
map.update(data)
}
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.