Namecount

Namecount is a metric used in data analysis and onomastics to quantify names within a dataset. It can refer to either the frequency of a particular name or to the number of distinct name strings observed.

In practice, namecount is used to measure name diversity in populations, track common names over time, or assess data quality by identifying duplicates.

Calculation typically involves normalization: convert to a consistent case, remove leading/trailing whitespace, normalize Unicode (NFKC/NFKD), and remove punctuation where appropriate. For distinct-name counts, a set of normalized names is tallied; for a given name, a simple count of matching entries is kept. In some contexts, alias or nickname mapping is used to group variants (e.g., "Bob" and "Robert").

Examples: In a dataset with "Alice Smith", "alice smith", "Bob Chen", "Alice Smith", the distinct name count after normalization is 2; the count for "Alice Smith" is 3.

Limitations include cultural naming conventions, diacritics, hyphenated or multi-part names, nicknames, script variations, and privacy concerns in real datasets.

Related concepts include name frequency analysis, deduplication, and data normalization.