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Nicolas Lambert
Hi. I'm Nicolas Lambert, research engineer in geographic information science at CNRS (France). My job is to draw maps and teach cartography at the university. I am a geographer 🌎, and not really a developer 🖥️
Public
Edited
Jul 7, 2023
1 fork
5 stars
2
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lc = require("linearcorrelation")
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geom = FileAttachment("world.geojson").json()
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data = FileAttachment("basics.csv").csv({ typed: true })
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bertin = require("bertin")
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Plot.plot({
grid: true,
x: {
type: xlog ? "log" : undefined
},
marks: [
Plot.dot(data, {
x: "gdppc",
y: "esp",
fill: "#53a6c9",
tip: true,
title: (d) => [d.name, "esp: " + d.esp, "gdppc: " + d.gdppc].join("\n")
})
]
})
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lc.test(data, { x: "gdppc", y: "esp", logx: true })
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Plot.plot({
grid: true,
x: {
type: xlog ? "log" : undefined
},
marks: [
Plot.dot(data, {
x: "gdppc",
y: "esp",
fill: "#53a6c9",
tip: true,
title: (d) => [d.name, "esp: " + d.esp, "gdppc: " + d.gdppc].join("\n")
}),
Plot.linearRegressionY(data, {
x: "gdppc",
y: "esp",
stroke: "#783c74"
})
]
})
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residuals_norm = regression.data.map((d) => d.residuals_norm)
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SimpleLinearRegression = import(
"https://cdn.skypack.dev/ml-regression-simple-linear@2.0.3?min"
).then((d) => d.default)
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reg = new SimpleLinearRegression(x, y)
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reg.toString()
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reg.score(x, y)
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ss = require("simple-statistics")
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sample = data2.map((d) => [d.gdppc_log, d.esp])
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corr = ss.sampleCorrelation(x, y)
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lm = ss.linearRegression(data2.map((d) => [d.gdppc_log, d.esp]))
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linearRegressionLine = ss.linearRegressionLine(lm)
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+ss.rSquared(sample, linearRegressionLine).toFixed(4)
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d3 = require("d3", "d3-regression")
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linearRegression = d3
.regressionLinear()
.x((d) => d.gdppc_log)
.y((d) => d.esp)
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espgdpregression = linearRegression(data2)
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