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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.

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.

Key Performance Indicators (KPIs)

  1. Unique Customer Locations:

    • Count of customers based on cities where customers are located.
    • Customer Count

  2. Order Trends:

    • Calculate the total number of orders placed during specific years, e.g., 2018.
    • Order Count

  3. Sales Analysis:

    • Analyze sales trends over the years.
    • Sales Per Year

Technologies Used

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