This example demonstrates how cosine similarity measures the resemblance between coin collections, quantifying the closeness of three people’s holdings. It shows the similarity scores computed for pairs of collections, revealing which individuals’ coin distributions are most alike. The code defines a `similarity` function that calculates the dot product of shared coin counts divided by the product of their Euclidean magnitudes, using Python’s `math.sqrt` and dictionary operations. It compares three hard-coded dictionaries—`you`, `me`, and `abby`—each mapping coin types to counts, and prints the resulting similarity values.