Exploratory Data Analysis (EDA) with python

In this project, I performed a comprehensive Exploratory Data Analysis (EDA) using a professional Python stack, including Pandas, NumPy, and Matplotlib. The workflow involved rigorous data cleaning to handle missing values and inconsistencies, followed by statistical profiling to uncover underlying patterns and distributions. Using advanced visualization libraries like Seaborn and, I created interactive heatmaps and correlation matrices to identify key relationships between variables. This process ultimately transformed raw, unstructured data into a "model-ready" dataset, providing actionable insights and a solid foundation for further predictive modeling.