tasks/D8_csv_cleanup/spec.md

D8: CSV Data Cleanup

Goal

Clean a messy CSV file (data/raw.csv) by fixing 5 data quality issues and produce a clean output at data/clean.csv.

Hard Requirements

1. Remove duplicate rows: Rows with identical values in the id column — keep the first occurrence.
2. Drop empty columns: Any column where every value is empty must be removed entirely.
3. Normalize date formats: The date column contains mixed formats (MM/DD/YYYY, YYYY-MM-DD, DD-Mon-YYYY). Normalize all to YYYY-MM-DD.
4. Strip whitespace: Trim leading/trailing whitespace from all string cells.
5. Fix delimiter errors: Some rows use semicolons instead of commas. Parse them correctly.

Output Format

• File: data/clean.csv
• Encoding: UTF-8
• Delimiter: comma
• Header row preserved (minus dropped columns)
• Sorted by id ascending (numeric sort)

Script

• Write or fix clean.py so that python clean.py produces the output.

Deliverables

• Working clean.py
• Correct data/clean.csv
• Verifier confirms all 5 issues resolved.