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Data Analysis with Python | Detection and Treatment of Outliers-Session 8

In this Python tutorial, you'll learn how to effectively detect and treat outliers, a crucial step in data analysis. We’ll begin with visual methods using Seaborn and Matplotlib to create box plots and normal distribution curves for identifying anomalies. Once we've detected outliers, we'll explore treatment methods, including percentile-based approaches, log transformations, and more. This tutorial will equip you with practical Python skills to handle outliers, ensuring your analysis is both accurate and reliable.