Stats | Art | Data Science | SciComm | Teaching
Unlisted
Edited
Feb 24
penguins
Plot.plot({
symbol: { legend: true },
//ggplot()
marks: [
Plot.dot(penguins, {
x: "body_mass_g",
y: "flipper_length_mm",
fill: "species",
r: 10,
opacity: 0.5,
tip: true,
mixBlendMode: "multiply",
symbol: "species"
})
]
})
Plot.plot({
color: { legend: true },
marks: [
Plot.raster(penguins, {
x: "flipper_length_mm",
y: "body_mass_g",
interpolate: "random-walk",
fill: "species"
}),
Plot.dot(penguins, {
x: "flipper_length_mm",
y: "body_mass_g",
fill: "species",
stroke: "white"
})
]
})
industries
Plot.plot({
color: { scheme: "BuGn" },
marks: [
Plot.areaY(industries, {
x: "date",
y: "unemployed",
fill: "industry",
tip: true
}),
Plot.ruleY([0])
]
})
import {us, power_plants} from "@observablehq/us-energy-mix-bubble-map-recreation"
states = topojson.feature(us, us.objects.states)
power_plants
viewof pickSource = Inputs.radio(
power_plants.map((d) => d.primary_source),
{
label: "Select one",
value: "solar",
unique: true
}
)
Plot.plot({
color: { legend: true, range: ["gray", "red"] },
r: { range: [0.5, 12] },
projection: "albers-usa",
marks: [
Plot.geo(states, { fill: "#ccc", stroke: "white" }),
Plot.dot(power_plants, {
x: "longitude",
y: "latitude",
r: "total_capacity",
fill: (d) => d.primary_source === pickSource,
tip: true,
sort: { channel: "fill" }
})
]
})
// primary_source
// total_capacity
// change the r option to update the radius
// Update this to be a bubble map where the size of dots corresponds to total capacity, and the color (fill) of dots is determined by the source
Plot.plot({
marks: [
Plot.dot(penguins, {
x: "body_mass_g",
y: "flipper_length_mm",
fill: "species",
stroke: "white"
})
]
})
viewof pickRadius = Inputs.range([1, 20], {
label: "Pick a dot radius:",
step: 0.5,
value: 3
})
viewof pickColor = Inputs.radio(["red", "green", "gold"], {
label: "Select color:",
value: "green"
})
pickColor
Plot.plot({
marks: [
Plot.dot(cars, {
x: "power (hp)",
y: "economy (mpg)",
fill: pickColor,
r: pickRadius
})
]
})
industries
Plot.plot({
marks: [
Plot.ruleY([0]),
Plot.lineY(industry_sub, {
x: "date",
y: "unemployed",
stroke: "industry",
tip: true
})
]
})
chooseIndustry
height = 500
width = 500
marginBottom = 20
marginTop = 20
marginLeft = 20
marginRight = 20
color = d3.scaleOrdinal(
penguins.map((d) => d.species),
d3.schemeCategory10
)
y = d3
.scaleLinear()
.domain(d3.extent(penguins, (d) => d.flipper_length_mm))
.nice()
.range([height - marginBottom, marginTop])
x = d3
.scaleLinear()
.domain(d3.extent(penguins, (d) => d.body_mass_g))
.nice()
.range([marginLeft, width - marginRight])
myChart = {
const svg = d3.create("svg").attr("width", width).attr("height", height);
svg
.append("g")
.selectAll("circle")
.data(penguins)
.join("circle")
.transition()
.duration(1000)
.delay((d, i) => i * 20)
.ease(d3.easeElastic)
.attr("cx", (d) => x(d.body_mass_g))
.attr("cy", (d) => y(d.flipper_length_mm))
.attr("fill", (d) => color(d.species))
.attr("r", 4);
return svg.node();
}
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