Exploratory Data Analysis (EDA) is a crucial initial step in data analysis, offering insights into dataset structure, patterns, and relationships. Using stats and data viz tools, EDA uncovers hidden patterns, outliers, and variable distributions. It informs analysis decisions, guiding hypothesis formulation and data prep. Common EDA steps include data cleaning, stats computation, visualization, and hypothesis testing. This repo is a collection of EDA projects. Most, if not all, datasets come from Kaggle.