A practical workflow for cleaning messy CSV files before JSON conversion

A repeatable cleanup workflow

Before parsing, preserve the original file. Then normalize headers, trim whitespace, standardize empty values, validate email/date fields, and deduplicate using the business key rather than the full row. Export a clean CSV and JSON only after recording rejected rows and reasons.

A small local Python starter kit is available here: https://vntrstds-spec.github.io/csv-cleanup-kit/

If a dataset needs hands-on cleanup instead, the page also has a transparent flat-rate 24-hour human cleanup option (CSV deduplication, header/date normalization, validation, and CSV-to-JSON).