Hierarchical Clustering — segments with a family tree In Minutes

What's in the report?

Standard-library analysis: agglomerative hierarchical clustering on standardized features. Unlike k-means, the full cluster tree is built first — structure at every scale — and only then cut, with the number of segments chosen by average silhouette width and cross-checked against the tree's own merge-height gaps. Ward.D2 linkage for compact interpretable groups, three linkages compared by cophenetic correlation, profiles as a z-score heatmap, a 2-D map, and every segment illustrated with named example rows. Works on any dataset: map 2 or more numeric columns plus a label column.