Public
Edited
Dec 14, 2022
1 star
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Plot.plot({
width: 1250,
marginBottom: 50,
marks: [
Plot.barY(GDPdata, {
x: "Country or Area",
y: "2018",
sort: { x: "y", reverse: true, limit: 10 }
}),
Plot.ruleY([0])
]
})
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Gini Coeffecients - Income Inequality Table.csv
Type Table, then Shift-Enter. Ctrl-space for more options.

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countries = GoogleTrendData.map(x => x.Country).sort((a,b) => {
return a.localeCompare(b)
})
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searchIndex = GoogleTrendData.findIndex((ob) => ob.Country==country)
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GoogleTrendData = FileAttachment("GoogleTrend2018-FIFA@3.csv").csv()
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Plot.plot({
width: 1250,
marginBottom: 50,
marks: [
Plot.barY(NewUrbanData, {
x: "Country Name",
y: Number("2018 [YR2018]"),
sort: { x: "y", reverse: true, limit: 10 }
}),
Plot.ruleY([0])
]
})
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UrbanData = FileAttachment("Urban Population - Urbanization.csv").csv()
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NewUrbanData = UrbanData.slice(0, 265)
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