What are some effective data cleaning tips for Jupyter Notebook?
Here are some tips: 1. Use Pandas for data manipulation, 2. Handle missing values with fillna(), 3. Remove duplicates with drop_duplicates().
How can I handle missing values more effectively?
You can use methods like interpolation, or fillna() with mean, median, or a specific value to handle missing data.
What about outliers? How should I deal with them?
You can identify outliers using IQR or Z-score methods and then decide whether to remove or transform them.
Can you suggest some libraries that help with data cleaning?
Sure! Besides Pandas, you can use libraries like NumPy for numerical operations and OpenRefine for more complex cleaning tasks.
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