E-commerce Data Analysis Project

Overview

This project is a Python and SQL-based analysis of e-commerce data, designed to extract meaningful insights and key performance indicators (KPIs) from a MySQL database. By integrating SQL queries with data visualization tools, the project aims to provide a detailed understanding of customer behavior, order trends, and other critical business metrics.

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Key Features

• Database Connection: Seamless integration with a MySQL database for querying e-commerce data.
• Data Exploration: Insights into customer locations, order trends, and other essential metrics.
• Visualization: Use of matplotlib and seaborn for visual representation of data.

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Key Performance Indicators (KPIs)

1. Unique Customer Locations:

   • Count of customers based on cities where customers are located.
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2. Order Trends:

   • Calculate the total number of orders placed during specific years, e.g., 2018.
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3. Sales Analysis:

   • Analyze sales trends over the years.
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Technologies Used

• Programming Language: Python
• Database: MySQL
• Libraries:
  • pandas for data manipulation.
  • matplotlib and seaborn for visualization.
  • mysql.connector for database connectivity.