Public
Edited
Jan 16, 2023
1 fork
2 stars
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Plot.plot({
marks: [
Plot.dot(penguins, {x: "culmen_length_mm", y: "culmen_depth_mm", stroke: "species"}), // try changing "stroke" to "fill"
Plot.linearRegressionY(penguins, {x: "culmen_length_mm", y: "culmen_depth_mm", stroke: "species"})
],
ariaLabel: "Penguin culmen dimensions",
ariaDescription: "Scatterplot of culmen length by culmen depth for three penguin species. Linear trendlines are added to each, revealing similar positive linear trends between culmen length and depth for chinstrap, gentoo and Adelie penguins."
})
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viewof myVal = Inputs.range([1, 10], {label: "Amount", step: 0.1, value: 3})
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myVal
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Plot.plot({
marks: [
Plot.dot(cars, {
x: "power (hp)",
y: "economy (mpg)",
fill: "steelblue",
opacity: 0.5,
r: myVal
})
],
ariaLabel: "Car horsepower and gas mileage",
ariaDescription: "Scatterplot showing the inverse relationship between car horsepower and gas mileage."
})
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Purpose-built for displays of data

Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
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