pixel flipper, data sifter. trying to see what I can while I'm here
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 WorldwideMassachusetts Coronavirus Cases by TownChoropleth 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 processReviewing 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
Nextstrain Prototyping - Issue 817
dateRange = d3.timeDay.range(new Date(start_date), d3.timeDay.offset(new Date(end_date),1)).map(d3.timeFormat("%Y-%m-%d"))
pivotNodes = function(pivot){
let rolledup = d3.rollup(nodes,
// we return the list of nodes as a Map
v => v.length || 0,
// first we group by the date as a string
d => numericToCalendar(d.data.node_attrs.num_date.value),
// then we group by the division
d => d.data.node_attrs[pivot].value
)
let keys = pivotKeys(pivot)
// this is me not being super familiar with d3.stack and using maps
// I'm going to create empty entries for missing divisions/date combinations
dateRange.forEach(d => {
let m = rolledup.get(d)
if(!m) {
m = new Map()
}
keys.forEach(key => {
if(!m.get(key)) {
m.set(key, 0)
}
})
rolledup.set(d, m)
})
return rolledup
}
// gives us an array with one row for each division, each of those rows is an array of 85 dates
pivotSeries = function(pivot, stackOrder) {
let keys = pivotKeys(pivot)
let pivotedNodes = pivotNodes(pivot)
// create an intermediate datastructure that we can pass into d3.stack
let entries = Array.from(pivotedNodes)
.sort((a,b) => a[0].localeCompare(b[0])) // order by date ascending
.map(d => ({ date: d[0], map: d[1] })) // store each element as an object instead of array
let stacked = d3.stack()
.keys(keys)
.value((group, key) => {
return group.map.get(key)
})
if(stackOrder) {
stacked = stacked.offset(stackOrder)
}
stacked = stacked(entries)
// post-processing the stack so that each datapoint (what will become a rectangle or a piece of the stream)
// has all it's associated metadata in the .data property,
// this way we don't need to look it up by index later
// I wonder if there is a way to do this with d3.stack
keys.forEach((key,i) => {
let stack = stacked[i];
stack.forEach(s => {
let d = s.data
s.data = {
date: d.date,
key: key,
group: regionsBy[pivot].get(key),
value: d.map.get(key),
color: colorScales[pivot](key)
}
})
})
return stacked
}
stackedHisto = function(data, height) {
let div = html`
<style>
.axis {
pointer-events: none;
}
</style>
<div clas="root">
<svg></svg>
</div>
`
let className = "sh_tooltip"
let tooltipDiv = makeTooltip(className)
div.appendChild(tooltipDiv)
const tooltip = d3.select(tooltipDiv).select("." + className)
// let points = pointsByDate(data)
// const svg = d3.create("svg")
const svg = d3.select(div).select("svg")
.attr("viewBox", [0, 0, width, height]);
/*
Setup interactive rectangles in the background to trigger highlight and tooltip
*/
svg.append("g")
.selectAll("rect.bg")
.data(dateRange)
.join("rect")
.classed("bg", true)
.attr("x", d => x(d))
.attr("y", d => margin.top)
.attr("width", x.bandwidth() )
.attr("height", d => height - margin.bottom)
.style("fill", "#fff")
.on("mouseover", function(d) {
d3.select(this).style("fill", "#dfdfdf")
tooltipDiv.update(this, d, data)
// tooltipDiv.update(this, d, points[d].points, points[d].total)
})
.on("mouseout", function(d) {
d3.select(this).style("fill", "#fff")
let ee = d3.event.toElement
console.log(tooltip.node().contains(ee))
// TODO: simplify this and move it to tooltip
if(!tooltip.node().contains(ee) &&
//ee != tooltip.node() &&
!d3.select(ee).classed("bg")) {
tooltip.style("display", "none")
}
})
let ys = d3.scaleLinear()
.domain([0, d3.max(data, d => d3.max(d, d => d[1]))]).nice()
.range([height - margin.bottom, margin.top])
svg.append("g")
.selectAll("g")
.data(data)
.join("g")
.attr("fill", (d) => {
return d[0].data.color.color
})
.style("pointer-events", "none")
.call((g,div) => {
return g.selectAll("rect")
.data(d => { return d})
.join("rect")
.attr("x", (d) => {
return x(d.data.date)
})
.attr("y", (d,i) => ys(d[1]))
.attr("width", x.bandwidth())
.attr("height", (d,i) => {return ys(d[0]) - ys(d[1])})
});
/* Axis and grid lines */
svg.append("g").classed("axis", true)
.attr("transform", `translate(${+x.bandwidth()/2 - .5},${height - margin.bottom})`)
.call(xAxisLines(dateRange, height, margin, "#dfdfdf"));
svg.append("g").classed("axis", true)
.attr("transform", `translate(${-x.bandwidth()/2 - .5},${height - margin.bottom})`)
.call(xAxisLines(xTicks, height, margin, "#999"));
svg.append("g").classed("axis", true)
.attr("transform", `translate(${-x.bandwidth()/2 - .5},${height - margin.bottom})`)
.call(xAxis);
svg.append("line").classed("axis", true)
.attr("x1", x(start_date))
.attr("x2", x(end_date) + x.bandwidth())
.attr("y1", height - margin.bottom)
.attr("y2", height - margin.bottom)
.style("stroke", "#dfdfdf")
svg.append("line").classed("axis", true)
.attr("x1", x(start_date))
.attr("x2", x(end_date) + x.bandwidth())
.attr("y1", height - margin.bottom)
.attr("y2", height - margin.bottom)
.style("stroke", "#dfdfdf")
// svg.append("g")
// .call(yAxis);
// return svg.node();
return div
}
stackedHisto(divisionSeries, height2)
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