pandas-cleaning

What problem does it solve?

Messy tabular data with inconsistent headers, mixed types, and many nulls is cleaned and standardized.

Core Features & Use Cases

• Column normalization to snake_case for consistent downstream processing.
• Type coercion for numeric, datetime, and boolean columns, with robust handling of mixed types.
• Null handling and deduplication to produce reliable datasets ready for analysis.
• Output polished .xlsx files with professional OpenPyXL formatting.

Quick Start

Run the pandas-cleaning workflow on a messy_input.csv to generate clean_output.xlsx with labeled headers and formatted cells.