Arik Chakma
274082fd77
* refactor: clean to roadmap content * refactor: move shared helpers into scripts/lib
9 lines
713 B
Markdown
9 lines
713 B
Markdown
# Data Cleaning
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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.
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Visit the following resources to learn more:
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- [@article@Complete Guide to Data Cleaning in Python](https://www.dataquest.io/guide/data-cleaning-in-python-tutorial/)
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- [@article@Pandas Data Cleaning](https://www.w3schools.com/python/pandas/pandas_cleaning.asp)
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- [@video@Data Cleaning in Pandas | Python Pandas Tutorials](https://www.youtube.com/watch?v=bDhvCp3_lYw) |