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This project focuses on analyzing customer purchase behavior from an e-commerce dataset. You will use Python, Pandas, SQL, and Matplotlib/Seaborn to: Extract meaningful insights from transactional data Identify trends in customer spending Visualize data to understand buying patterns

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Customer Purchase Analysis

This project analyzes an e-commerce dataset, cleans data, and extracts insights.

Steps:

  1. Setup Database: Load data into SQLite (database_setup.py).
  2. Clean Data: Remove duplicates, fill missing values (data_processing.py).
  3. Analyze Data: Calculate revenue, top customers (analysis.py).
  4. Visualize: Plot trends (visualization.py).

Usage:

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This project focuses on analyzing customer purchase behavior from an e-commerce dataset. You will use Python, Pandas, SQL, and Matplotlib/Seaborn to: Extract meaningful insights from transactional data Identify trends in customer spending Visualize data to understand buying patterns

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