Data Cleaning Techniques
Last updated June 12, 2024
Data cleaning is an essential step to ensure the quality and accuracy of your data. Here are some common techniques to help you clean your dataset effectively.
Steps for Data Cleaning
- Identify and handle missing values
- Remove duplicate records
- Correct structural errors
- Filter out outliers
- Normalize and standardize data
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