chart = {
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height]);
svg.append("g")
.call(xAxis);
svg.append("g")
.call(yAxis);
svg.append("g")
.selectAll("circle")
.data(data)
.join("circle")
.filter(d => d.body_mass_g)
.attr("cx", d => x(d.flipper_length_mm))
.attr("cy", d => y(d.body_mass_g))
.attr("r", 4);
return svg.node();
}
data = [
{ model: "small", params: 76961152, training_time: 140.94 },
{ model: "base", params: 247577856, training_time: 490.93 },
{ model: "large", params: 783150080, training_time: 0 },
{ model: "xl", params: 0, training_time: 0 },
{ model: "xxl", params: 0, training_time: 0 }
]
height = 400
x = d3.scaleLinear()
.domain(d3.extent(data, d => d.flipper_length_mm)).nice()
.range([margin.left, width - margin.right])
y = d3.scaleLinear()
.domain(d3.extent(data, d => d.body_mass_g)).nice()
.range([height - margin.bottom, margin.top])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x))
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y))
margin = ({top: 25, right: 20, bottom: 35, left: 40})
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.
