Drop and Replace Null & Duplicate Values in Python | Data Cleaning
In this video, learn how to clean your dataset by dropping and replacing null (NaN) values and removing duplicate entries using Python. This is an essential step in the data preprocessing pipeline for any data science or machine learning project.
We cover:
✅ How to identify and handle missing data
✅ Filling null values with mean, median, or mode
✅ Dropping rows/columns with NaNs
✅ Detecting and removing duplicates
This hands-on tutorial is perfect for beginners and aspiring data scientists!
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