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Learning Observable
Edited
Sep 27, 2023
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Learning Observable
IntroductionNotebooks and cellsGetting data into ObservableData visualization with Chart cell
Observable Plot
Cell modes, reactive Markdown, and HTMLReactive dataflowUser inputs and interactivityJavaScript and ObservableImporting and remixing cells and notebooks
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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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Plot.plot({
marks: [
Plot.rectY(olympians, Plot.binX({y: "count"}, {x: "weight"})),
Plot.ruleY([0])
]
})
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Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
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