Advanced Python Data Exploration & Automated Reporting

Executed a comprehensive, end-to-end data analysis project in Python using Object-Oriented Programming (OOP) concepts and robust exception handling. Handled advanced data cleaning by addressing missing values, outliers, duplicate records, and inconsistent data formats, including standardizing dates, casting numeric columns, and trimming text. Built modular, reusable preprocessing pipelines alongside engineered features such as Profit Margin, Shipping Duration, and Sales Performance Category. Conducted thorough exploratory and statistical data analysis, including correlation matrices, distribution assessments, and trend tracking. Designed 8+ advanced visualizations using Matplotlib and Seaborn, generated automated KPI summaries, optimized DataFrame memory usage and execution performance, and automated the final export of cleaned datasets and visual reports.