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Observable Plot Course
Edited
Oct 26, 2023
25 forks
7 stars
6
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Plot.plot({
marks: [
Plot.dot(wb2010, { x: "gdp", y: "life_exp", fill: "gray"})
],
x: {type: "log"},
margin: 50
})
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Plot.plot({
marks: [
Plot.lineY(stocks, {
x: "Date",
y: "Close",
stroke: "symbol"
})
],
color: { legend: true }
})
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Plot.plot({
marks: [
Plot.dot(wb, {
x: "gdp",
y: "co2",
fill: "country_name",
r: "gdp",
})
],
x: { type: "log" },
y: { type: "log" },
r: { range: [3, 20] }
})
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plants
Type Table, then Shift-Enter. Ctrl-space for more options.

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Plot.plot({
marks: [
Plot.barX(plants,
Plot.groupY(
{ x: "sum" },
{
x: "total_capacity",
y: "state",
fill: "primary_source",
sort: { y: "x", reverse: true, limit: 10 }
}
)
),
Plot.ruleX([0])
],
marginLeft: 100
})
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Power_Plants.csv
SELECT
Longitude as longitude
, Latitude as latitude
, Plant_Name as plant
, City as city
, County as county
, StateName as state
, Total_MW as total_capacity
, (case when PrimSource = 'petroleum' then 'oil'
when PrimSource = 'geothermal' then 'other'
when PrimSource = 'biomass' then 'other'
when PrimSource = 'pumped storage' then 'other'
when PrimSource = 'batteries' then 'other'
else PrimSource end) as 'primary_source'
FROM "Power_Plants"
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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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