Engineer & data visualization lover | Tae Bo Enthusiast
Public
Edited
Apr 2, 2023
us = FileAttachment("us-counties-10m.json").json()
us_power_plants = FileAttachment("us_power_plants.csv").csv()
us_power_plants
Type Table, then Shift-Enter. Ctrl-space for more options.
viewof selectedEnergy = Inputs.select(us_power_plants,
Plot.plot({
projection: "albers-usa",
marks: [
Plot.geo(states, {
fill: "white", stroke: "#e2e2e2"
}),
Plot.dot(us_power_plants, {
x: "longitude",
y: "latitude",
r: "Total_MW",
fill: "PrimSource",
opacity: .5
}),
Plot.dot(us_power_plants, {
x: "longitude",
y: "latitude",
r: "Total_MW",
filter: d => d.Total_MW > 3500,
fill: "PrimSource",
stroke: "black"
}),
Plot.text(us_power_plants, {
x: "longitude",
y: "latitude",
text: "Plant_Name",
filter: d => d.Total_MW > 3500,
stroke: "white",
fill: "black",
textAnchor: "start",
dx: 20,
fontSize: 12,
fontWeight: 600
})
],
r: {range:[1, 15]},
color: {legend: true},
height: 500,
width: 800,
margin: 50
})
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.
