Data Cleaning in Pandas | Handle Missing Values in Python | Data Science Lecture 18

@techlearningwithRajat
🔥 Welcome to Lecture 18 of Python Data Science Series

In this video, we will learn Data Cleaning and Missing Value Handling in Pandas with complete practical examples.

📘 Topics Covered:
✅ What is Data Cleaning
✅ Missing Values in Pandas
✅ NaN Values
✅ isnull() Function
✅ sum() Function
✅ dropna() Function
✅ fillna() Function
✅ Mean, Median & Mode
✅ Forward Fill & Backward Fill
✅ Removing Duplicate Data
✅ replace() Function
✅ rename() Function
✅ astype() Function
✅ Real-Life Data Cleaning Examples

This lecture is perfect for:
🎯 Python Beginners
🎯 Data Science Students
🎯 Machine Learning Learners
🎯 College Students

💻 Tools Used:
✔ Python
✔ Pandas
✔ VS Code

📌 Practice all examples while watching the tutorial for better understanding.

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