pizzaOrders-2.csv
Type Table, then Shift-Enter. Ctrl-space for more options.
Plot.plot({
marks: [
Plot.ruleY([0]),
Plot.lineY(pizza, {x: "total", y: "unit_price", stroke: "Category"})
]
})
Plot.plot({
title: "How does price affect quantity..." ,
height: 1000,
width: 1000,
marginLeft: 40,
marginRight: 30,
marginTop: 70,
marginBottom: 60,
style:{fontSize: 20},
marks: [
Plot.density(pizza, {x: "total", y: "unit_price" })
]
})
Plot.plot({
title: "How does price affect quantity..." ,
height: 1000,
width: 1000,
marginLeft: 40,
marginRight: 30,
marginTop: 70,
marginBottom: 60,
style:{fontSize: 20},
marks: [
Plot.dot(pizza, {x: "total", y: "unit_price"})
]
})
Plot.plot({
marks: [
Plot.tickX(pizza, {x: "total", y: "unit_price"})
]
})
Plot.plot({
height: 180,
marks: [
Plot.dot(cars, Plot.dodgeY({x: "weight (lb)"}))
]
})
Plot.plot({
color: {
scheme: "ylgnbu"
},
marks: [
Plot.hexagon(olympians, Plot.hexbin({}, {x: "weight", y: "height"}))
]
})
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.
