Bitemporal coronavirus casesSensitivity and Specificity (sketch)Coronavirus orbitsSmoothing with simple moving average vs. binomial filterCoronavirus logistic isoplethsRecreating John Burn-Murdoch’s Coronavirus trackerBuilding up to John Burn-Murdoch’s Coronavirus trackerCovid Tracking Project data
Variance
dist = (array, scale) => {
const stdev = scale || Math.sqrt(d3.variance(array));
const mean = d3.mean(array);
const x = x => (50 * (x - mean)) / stdev;
return html`<span style="position: relative;">
${mean.toFixed(0)}${array.map(
(d, i) =>
html`<span style="
position: absolute;
top: ${x(d)}px;
left: ${x(d)}px;
opacity: .3;
z-index: -1;
">
${d}
</span>`
)}</span>`;
}
data = Array.from(
getCovidDataGrouped({
statistic: "positive",
derivative: 1
}).entries()
)
.map(([state, map]) => ({
state,
name: stateNames.get(state),
data: Array.from(map.entries())
.map(([date, value]) => value)
.filter(value => value !== undefined)
}))
.sort((a, b) => a.name.localeCompare(b.name))
scale = d3.mean(data.map(({ data }) => d3.deviation(data)))
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