xValues = pizza.map(d => d.order_date);
yValues = pizza.map(d => d.orders);
colorScale = d3.scaleLinear().domain([Math.min(...yValues), Math.max(...yValues)])
Plot.plot({
color: {
scheme: "Cubehelix",
legend: true
},
width: width,
height: 420,
marginRight: 120,
marks: [
Plot.frame(),
Plot.lineY(pizza, Plot.binX({y: 'sum'}, {
x: "order_date",
y: "orders",
stroke: d => colorScale(d.orders),
z: "name",
interval: d3.utcWeek,
tip: true
})),
]
})
Plot.plot({
color: {
scheme: "ylorrd",
legend: true
},
width: 720,
height: 300,
marginLeft: 90,
facet: {
data: pizza,
y: "pizza_name",
x: "size",
},
marks: [
Plot.tickX(
pizza,
Plot.binX(
{
fill: "sum",
},
{
x: "order_date",
stroke: "orders",
interval: d3.utcWeek
}
)
),
Plot.frame({ stroke: "#aaa", strokeWidth: 0.5 })
]
})
categorical = Plot.plot({
colors: {
scheme: "categorical10",
legend: true
},
width: 720,
height: 420,
facet: {
data: pizza,
y: "pizza_name",
x: "size",
marginRight: 90,
label: ""
},
marks: [
Plot.areaY(pizza, Plot.binX({y: 'sum'}, {
x: "order_date",
y: "orders",
fill: "category",
interval: d3.utcWeek,
tip: true
})),
Plot.ruleY([0])
],
})
pizza
Type Table, then Shift-Enter. Ctrl-space for more options.
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.
