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Regex for Data Cleaning: Practical Patterns for Messy Real-World Data

Regex for Data Cleaning: Practical Patterns for Messy Real-World Data

Real-world data — phone numbers, dates, emails, log entries, product codes — arrives inconsistently. Here are the regex patterns for the most common data cleaning tasks: phone normalisation, date standardisation, HTML stripping, whitespace cleaning, and log redaction.

Jun 9, 2026