📉 Fix Skewed Data in Python: 5 Transformations You Should Know!

Video Description

📉 Fix Skewed Data in Python: 5 Transformations You Should Know Skewed data can seriously impact your statistical analysis and machine learning models—but you can fix it with the right transformations. In this video, I demonstrate 5 powerful methods to clean skewed data using NumPy and SciPy: • ✔️ Square Root • ✔️ Cube Root • ✔️ Fourth Root • ✔️ Log Transformation • ✔️ Yeo-Johnson Transform (via scipy.stats) To help you compare, I also visualize the change in skewness after each transformation with a clear, easy-to-read bar plot. ⸻ 🧰 Tools Used: • numpy for numerical operations • scipy.stats for Yeo-Johnson transformation • matplotlib or seaborn for visualization Whether you’re building models or just exploring data, these techniques will help you make your distributions more normal—and your analysis more reliable. 🔔 Subscribe for more Python-based tips for data science, research, and real-world analytics!