Published
Edited
Apr 20, 2022
3 stars
Food clockDisambiguating selection in a 2D treePerceptually more-uniform diverging color scatterplotDays since a U.S. President was last shotSingle-serving sitesDo you feel old?Dynamic scales deprive dashboards of institutional memoryNesting chevron pillsColumnar group byDe Moivre by generatorsShowing ESPN Receiver Tracking Metrics using weighted radar chartsCombine consecutive stringsDollar spectrumThe Feedback BathtubIs Visnu’s hex random?Dual axes are a great way to show correlation 🔥Promise.raceHealthcare plan payoff curvePlot image beeswarmGenerations on Google TrendsFor i of myriadChatterjee correlationChecking invariance of round trip-0 and 0
Norms and central tendency
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rand = (reset, d3.randomLcg(6))
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transform = n => Math.round(Math.log(1 + n) * 500)
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data = (regenerate, d3.range(99).map(() => transform(rand())))
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counts = d3.rollups(data, arr => arr.length, d => d).sort((a, b) => b[1] - a[1])
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sumNorm = (v, norm) => d3.sum(data.map((d) => Math.abs(d - v) ** norm))
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minimizeNorm = (norm) => {
let minI = 0;
let minNorm = Infinity;
for (let i = 0; i < transform(1); i++) {
let normSum = sumNorm(i, norm);
if (normSum <= minNorm) {
minI = i;
minNorm = normSum;
}
}

return minI;
}
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mean = d3.mean(data)
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minimizeNorm(2)
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median = d3.median(data)
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minimizeNorm(1)
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mode = counts[0][0]
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minimizeNorm(0.0001)
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plotData = [...d3.range(-5, 0).map(d => Math.exp(d)), ...d3.range(1, 10)]
.map(norm => ({norm, value: minimizeNorm(norm)}))
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Plot.dot(plotData, { x: "norm", y: "value" }).plot({
x: { nice: true },
y: { nice: true },
height: 200
})
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// is the midpoint something?
(d3.max(data) - d3.min(data)) / 2 + d3.min(data)
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import {set} from "@observablehq/synchronized-inputs"
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