PLS Nigerian SMB Data Sanitizer
Python / PandasA production-grade Python data engineering pipeline for sanitizing and standardizing Nigerian SME transaction data — phone numbers, currency, dates, and duplicates, with a full quality report.
ProductOverview
This is the Community Edition, published as a free portfolio project, with a Pro Edition (larger example datasets, a dataset generator, a benchmark suite, and extended documentation) planned separately. The pipeline handles multi-encoding CSV ingestion (UTF-8, latin-1, cp1252) with automatic fallback, normalizes Nigerian phone numbers to E.164 format, strips Naira symbols and formatting from currency fields, standardizes mixed date formats to YYYY-MM-DD using fully vectorized pandas operations, and produces a per-field quality report after cleaning.
Editions
Community
- Phone number normalization (E.164)
- Currency cleaning (Naira symbols, commas, formatting)
- Mixed date-format standardization
- Configurable missing-value handling
- Duplicate removal + post-clean quality report
- CLI via argparse, structured logging, unit + integration tests
- 1,000-row example dataset included
Available Now
View on GitHubPro
- Everything in Community
- Enterprise-scale example datasets (10k / 50k / 100k rows)
- Dataset generator & benchmark suite
- Architecture & troubleshooting documentation
- Commercial license
Coming Soon
Web App
- Everything in Pro
- Live web dashboards
- Real-time data sync
- User role management
Coming Soon