The avatar for @kpivert
Kurtis Pivert
Interested in communicating data-driven insights. Director of Data Science at @ASNDataAnalytics.
Public
Edited
Jul 30, 2023
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maples = d3.csv(
"https://portal.edirepository.org/nis/dataviewer?packageid=knb-lter-hbr.157.3&entityid=5c415a399b00430d35d13c31312f1e53",
d3.autoType
)
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maples
Type Table, then Shift-Enter. Ctrl-space for more options.

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maples2003 = maples
.map((d) => ({
year: d.Year,
watershed: d.Watershed,
stemLength: d.StemLength,
leafMass: d.LeafDryMass,
stemMass: d["StemDryMass"],
leafArea: d.CorrectedLeafArea
}))
.filter((d) => d.year === 2003)
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PlotMatrix()
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ML = require("https://www.lactame.com/lib/ml/6.0.0/ml.min.js")
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maples2003LM_reference = new ML.SimpleLinearRegression(
maples2003_reference.map((d) => d.stemLength),
maples2003_reference.map((d) => d.stemMass)
)
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maples2003LM_calcium = new ML.SimpleLinearRegression(
maples2003_calcium.map((d) => d.stemLength),
maples2003_calcium.map((d) => d.stemMass)
)
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import { scale, asMatrix } from "@chrispahm/hierarchical-clustering"
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maples2003_scaled = scale(maples2003)
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maples2003_array = maples2003_scaled.map((d) => [
d.stemLength,
d.leafMass,
d.stemMass,
d.leafArea
])
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maples2003_kmeans = new ML.KMeans(maples2003_array, 2)
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maples2003DTC = maples2003.map((d, i) => ({
...d,
cluster_no: maples2003_kmeans.clusters[i]
}))
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Plot.plot({
color: { legend: true },
marks: [
Plot.text(maples2003DTC, {
x: "stemLength",
y: "stemMass",
text: "cluster_no",
stroke: "watershed",
fontWeight: 100,
fontSize: 15,
tip: true
})
]
})
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clusterCounts = d3.rollup(
maples2003DTC,
(v) => v.length,
(d) => d.watershed,
(d) => d.cluster_no
)
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maples2003_pca_scaled = scale(
maples2003.map(({ year, watershed, ...rest }) => rest)
)
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maples2003_pca_array = maples2003_pca_scaled.map(Object.values)
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// Noticed that the array I created for K means is not the same as that for PCA.
maples2003_array === maples2003_pca_array
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maples2003PCA = new ML.PCA(maples2003_pca_array)
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maples2003PCA.getExplainedVariance()
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maples2003PCA.getCumulativeVariance()
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viewof loadings
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viewof scores
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scaling_factor = 5
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