Super Store Sales Analytics Final Year Project Source Code

Super Store Sales Analytics is a Python-based final year project developed for analyzing retail sales data and predicting sales using machine learning. This major project uses the Kaggle Superstore Sales dataset to perform exploratory data analysis, statistical summary, missing-value checking, correlation analysis, comparison visualizations, and sales prediction. The project generates multiple graphs such as sales by region, sales by category, monthly sales trend, sales vs profit, segment comparison, top sub-categories, correlation heatmap, and actual vs predicted sales graph. It uses Random Forest and Linear Regression models for sales prediction and evaluates model performance using R², RMSE, and MAE. This Super Store Sales Analytics source code is suitable for students who need a final year project, major project, minor project, source code, and project report based on Python, data analytics, retail analytics, visualization, and machine learning