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Hello friends! 🙌 In this video, we will learn Data Cleaning in Python, which is a crucial step in Data Science. Real-world data is often messy (incomplete, inconsistent, missing values), and cleaning it is essential for accurate analysis and modeling.

🔹 Topics Covered in This Video:
✅ Handling missing values (dropna(), fillna())
✅ Removing duplicate data (drop_duplicates())
✅ Formatting data and cleaning unwanted characters
✅ Identifying and fixing outliers & incorrect data
✅ Using Pandas and NumPy for data cleaning

🎯 Who Should Watch This Video?
👉 Beginners in Data Science and Machine Learning
👉 Anyone looking to understand data preprocessing in Python
👉 Those who want to prepare clean data for analysis and modeling

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