What are best practices for cleaning and prepping data?
The question is about Data Analysis .
Best practices for cleaning and preparing data include: removing duplicates, managing missing values, and converting all data to a standard format. It’s crucial to scale numbers, turn categories into codes, and identify outliers that could influence the results. Proper data cleaning helps you get reliable insights. Whenever possible, these steps should be automated to improve speed and reduce errors.
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