Data Cleaning Plan
Published · Updated
Clean it in the right order, or you'll do half of it twice.
Tags: Data, Technical, Productivity
Prompt template
## Cleaning plan - The data: [textarea: Columns, types, and a sample of rows] - Where it came from: [textarea: System, export, survey, scraped, typed by hand] - Problems I've spotted: [multi: Duplicates, Missing values, Inconsistent formats, Outliers, Wrong types, Free text where categories should be, Encoding mess] - What it feeds: [textarea: The analysis or system downstream] - Tools: [dropdown: Spreadsheet, Python, R, SQL] - Rows: [text: Roughly] Give me the sequence, ordered to avoid rework. Deduplicating before standardising formats misses duplicates, so order matters more than technique here. Per problem: how to detect it, how to fix it, and what to do when the right answer is genuinely ambiguous. Be specific about missing values, since dropping and imputing lead to very different conclusions. End with the checks that prove the cleaned data is sound.