Public
Edited
Jun 6, 2023
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summary(cars, { ignoreNonNumeric: true })
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corMatrix = cor(cars)
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corrplot(corMatrix)
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cor(cars.map(row => row.Miles_per_Gallon), cars.map(row => row.Horsepower), {
test: true
})
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vari(cars.map(row => row.Cylinders))
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cov(cars.map(row => row.Miles_per_Gallon), cars.map(row => row.Horsepower))
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cov(
cars.map((row) => row.Miles_per_Gallon),
cars.map((row) => row.Cylinders)
)
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variancesAndCovariances = cov(cars)
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corrplot(variancesAndCovariances, { test: 'Covariance', domain: [-100, 100] })
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Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.

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View(variancesAndCovariances)
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View([[1, 2, 3], [3, 4, 5], [6, 7, 8, 9, 10]])
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hist(cars.map((car) => car.Cylinders))
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import { data } from "@d3/histogram"
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plot(dataset2)
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Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.

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plot([1, 2, 3])
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dataset2 = [
{ x: -3, y: 7.5 },
{ x: -2, y: 3 },
{ x: -1, y: 0.5 },
{ x: 0, y: 1 },
{ x: 1, y: 3 },
{ x: 2, y: 6 },
{ x: 3, y: 14 }
]
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