Former physicist turned programmer with research experience building complex computational models for physical systems.
Public
Edited
May 19, 2023
data = FileAttachment("data.csv").csv()
plotJitterRegionsWorld1 = FileAttachment("plot-jitter-regions-world-1.png").image()
Plot.plot({
height:350,
marginLeft:100,
color:{domain:color_domain, range:color_range},
x:{domain:[0, 90]},
marks:[
Plot.frame(),
Plot.dot (data, Plot.groupY({ x:'mean'}, {x: "student_ratio", y:'region', fill:'region',sort:{y:'x'}, r:8})),
Plot.barX(data, Plot.groupY({x1:'mean'}, {x1: "student_ratio", x2:mean_ratio, y:'region', fill:'region', insetTop:20, insetBottom:20})),
Plot.dot(data, {y:'region', x: "student_ratio", fill:'region', opacity:.5}),
Plot.tickX([mean_ratio]),
// Plot.dot(data, Plot.dodgeY('middle',{x: "student_ratio", fill:'region', fy:'region', filter:'region'}))
]
})
Plot.plot({
height:350,
x:{domain:[0, 90]},
marginLeft:100,
marks:[
Plot.dot(data, Plot.dodgeY('middle',{x: "student_ratio", fill:'region', fy:'region', sort:{fy:'x'}})),
]
})
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.
