Agricultural economics · Thünen Institute of Farm Economics / University Bonn
Published
Edited
Jun 15, 2022
5 forks
Importers
25 stars
SummaryTable(seeds_df)
seeds_lookup = ({
1: "Kama",
2: "Rosa",
3: "Canadian"
})
seeds_label = seeds_df.map((row) => seeds_lookup[row["type of seed"]])
seeds_no_label_df = seeds_df.map(
({ "type of seed": undefined, ...headers }) => ({
...headers
})
)
seeds_df_sc = scale(seeds_no_label_df)
SummaryTable(seeds_df_sc)
dist_mat = dist(asMatrix(seeds_df_sc), distance.euclidean)
hclust_avg = new hclust(dist_mat, {
method: "average",
isDistanceMatrix: true
})
dendrogram(hclust_avg)
cut_avg = hclust_avg.group(3)
plot_dendrogram_3 = dendrogram(cut_avg, {
h: 3,
width: 500,
//height: 400,
hideLabels: true
})
clustered_groups = Object.entries(
cut_avg.children.reduce((lookup, group, groupIndex) => {
group.traverse((child) => {
if (child.index > -1) lookup[child.index] = groupIndex + 1;
});
return lookup;
}, {})
).map((arr) => arr[1])
seeds_df_clustered = seeds_df.map((row, index) => ({
...row,
cluster_result: clustered_groups[index]
}))
dendrogram(hclust_avg_simple, { h: 2.5 })
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.
