Senior Art Editor at Nature News in London.
Public
Edited
Oct 19, 2023
data = FileAttachment("20 Oct female academics fig4_gender-edit.csv").csv({
typed: true
})
data.columns
data.map((d) => d.category)
Plot.plot({
color: { legend: true },
y: { grid: true, domain: [0, 0.5] },
facet: {
data: data,
x: "category"
},
marks: [
Plot.frame(),
Plot.line(data, { x: "age_group", y: "percent", stroke: "gender" }),
Plot.dot(data, { x: "age_group", y: "percent", fill: "gender" })
]
})
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.
