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* refactor: clean to roadmap content * refactor: move shared helpers into scripts/lib
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Data Cleaning
Data cleaning identifies and resolves quality issues in raw data so it is accurate and consistent enough for analysis. In Python, cleaning is done primarily with Pandas and string processing tools. Common tasks include handling missing values, fixing data types, standardizing text, removing duplicates, and detecting outliers.
Visit the following resources to learn more: