A data-driven e-commerce sales analysis project using Python to uncover trends, customer insights, and product performance.
This project provides a complete end-to-end analysis of e-commerce sales data using Python. It includes data cleaning, exploration, and visual storytelling through graphs and charts. You'll explore monthly trends, customer segments, product performance, shipping modes, and regional performance to gain actionable business insights.
Ideal for data analysts and aspiring data scientists looking to strengthen their portfolios with real-world analytics.
- Python
- Pandas – Data manipulation
- Plotly – Data visualization
- Jupyter Notebook – Interactive development
ecommerce_sales_analysis.ipynb– Jupyter Notebook containing all steps:- Data loading and exploration
- Feature extraction from dates
- Grouping and aggregation for insights
- Visualizations for trends, performance, and behavior
- Monthly & yearly sales trends
- Top-selling products and categories
- Customer behavior by segment
- Region-wise performance