This project analyzes the Sample Superstore dataset using Python to uncover valuable business insights. The analysis includes data cleaning, exploratory data analysis (EDA), sales analysis, profit analysis, customer analysis, product analysis, time series analysis, and business recommendations.
- Analyze sales performance.
- Identify profitable products and categories.
- Discover customer purchasing patterns.
- Evaluate regional performance.
- Analyze shipping methods.
- Generate business insights through data visualization.
- Python
- Pandas
- Matplotlib
Python E-Commerce Sales Analysis/
├── main.py
├── Dataset/
├── Images/
├── README.md
├── requirements.txt
├── LICENSE
└── .gitignore
- Phase 1 – Project Setup & Data Loading
- Phase 2 – Data Understanding
- Phase 3 – Data Cleaning
- Phase 4 – Exploratory Data Analysis
- Phase 5 – Sales Analysis
- Phase 6 – Sales Visualization
- Phase 7 – Profit Analysis
- Phase 8 – Customer Analysis
- Phase 9 – Time Series Analysis
- Phase 10 – Product Analysis
- Phase 11 – Regional & Shipping Performance Analysis
- Phase 12 – Business Insights & Key Findings
- Phase 13 – Final Conclusion & Recommendations
- Data Cleaning
- Exploratory Data Analysis
- Business Intelligence
- Sales Analysis
- Profit Analysis
- Customer Analysis
- Product Analysis
- Time Series Analysis
- Data Visualization
- Business Recommendations
Project visualizations are available inside the Images folder.
Ahmar Ali
BS Statistics
Quaid-i-Azam University Islamabad