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Discover the most effective Data Cleaning prompts. High-quality templates curated by experts to help you get professional AI results.
Build a robust data cleaning pipeline for a messy CSV dataset. Requirements: 1. Handle missing values using forward-fill, backward-fill, and mean imputation strategies. 2. Detect and remove outliers using IQR method. 3. Standardize date formats across multiple columns. 4. Remove duplicate rows based on composite keys. 5. Generate a data quality report showing before/after statistics. Use pandas best practices with method chaining for readability.