synthdata-anonymize

What problem does it solve?

Replace real PII in a dataset with realistic synthetic equivalents while preserving row counts, column types, and statistical distributions. Detects names, emails, phones, SSNs, addresses, credit cards, and user-identifying columns via name heuristics + value patterns. Use this skill when the user wants to "anonymize this dataset", "scrub PII", "make this data safe to share", "de-identify real data", "create a synthetic copy", or needs a sharable version of production data without exposing individuals.

Core Features & Use Cases

• PII detection via name heuristics and value patterns
• Deterministic anonymization using Faker with a seed to preserve joins across tables
• Structure preservation maintains row counts, column types, and distributions
• Safe sharing scenarios supports de-identification for production-like datasets
• Multi-table workflows preserves foreign-key relationships when requested

Quick Start

Run a sample dataset through the anonymize pipeline to replace PII values with synthetic equivalents while keeping the original shape.