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Berkeley MIDS W209 Information Visualization Course
Published
Edited
Apr 13, 2021
2 forks
8 stars
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md`# JSON vs CSV`
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data = Array.from({ length: 300 }).map((d, i) => ({
name: `John ${i}`,
age: Math.floor(Math.random() * 120),
height: Math.random() * 2.0
}))
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csvText = `name,age,height
John,15,6.6
Andy,24,6.2
Drew,17,6`
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dataCSV = d3.csvParse(csvText, d3.autoType)

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jsonText = `[{"name":"John","age":15,"height":6.6},{"name":"Andy","age":24,"height":6.2},{"name":"Drew","age":17,"height":6}]`
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dataJSON = JSON.parse(jsonText)
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data3 = d3.json(
"https://gist.githubusercontent.com/john-guerra/a1bc0af51d76e620574ce47b1e8243e9/raw/9f0116d984f834cefa950d5e7c3cdaa4e431d59a/dataJSON.json"
)
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FileAttachment("data.csv")
.text()
.then(res => d3.csvParse(res, d3.autoType))
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d3.csvParse(await FileAttachment("data.csv").text(), d3.autoType)
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viewof myFile = html`<input type="file"/>`
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Files.text(myFile)
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viewof alsoMyFile = fileInput({
initialValue: FileAttachment("data.csv")
})
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d3.csvParse(await alsoMyFile.text())
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d3 = require("d3@6")
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import { fileInput } from "@mbostock/file-input-with-initial-value"
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One platform to build and deploy the best data apps

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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