Data Cleaning with Pandas for Beginners | Real-World Raw Dataset to Clean Data Step-by-Step (part 2) скачать в хорошем качестве

Data Cleaning with Pandas for Beginners | Real-World Raw Dataset to Clean Data Step-by-Step (part 2)

In this video, we clean a real messy employee dataset using Python and Pandas. The dataset contains: Missing values Duplicate employee IDs Incorrect data types Inconsistent department names Invalid salary values Mixed date formats We will clean it step-by-step using a structured data cleaning checklist. You will learn: ✔ How to inspect a dataset properly ✔ How to check and fix data types ✔ How to clean numeric columns ✔ How to standardize categorical values ✔ How to handle missing data ✔ How to remove duplicates ✔ How to convert date columns This tutorial is beginner-friendly and follows real industry practices. If you are learning Data Science or preparing for interviews, this video will help you understand how professionals approach data cleaning. Tools Used: Python Pandas Jupyter Notebook Don’t forget to like, comment, and subscribe if this helped you 🚀