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A data-driven e-commerce sales analysis project using Python to uncover trends, customer insights, and product performance.

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πŸ›’ E-commerce Sales Analysis & Visualization Using Python

πŸ“Œ About

A data-driven e-commerce sales analysis project using Python to uncover trends, customer insights, and product performance.


πŸ“˜ Project Description

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.


🧰 Tech Stack

  • Python
  • Pandas – Data manipulation
  • Plotly – Data visualization
  • Jupyter Notebook – Interactive development

πŸ“‚ Project File

  • e commerce project.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

πŸ“Š Key Insights Covered

Monthly & yearly sales trends

Top-selling products and categories

Customer behavior by segment

Region-wise performance

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A data-driven e-commerce sales analysis project using Python to uncover trends, customer insights, and product performance.

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