Advanced Python Data Exploration & Automated Reporting

Explored the Sample Superstore 2019 dataset using Pandas and NumPy, reviewing dataset structure, metadata, data types, and data quality. ● Performed data cleaning and preprocessing, investigated missing or duplicate records and inconsistent formats, and created reusable preprocessing steps. ● Engineered analytical features such as profit margin, shipping duration, and sales-performance categories; analyzed distributions, correlations, and trends. ● Created visualizations and automated KPI summaries/reports using Matplotlib and Seaborn. Technologies: Python, Pandas, NumPy, Matplotlib, Seaborn