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🛍️ Black Friday Dataset EDA & Feature Engineering

📌 Overview

This project explores the Black Friday Sales dataset and applies EDA + Feature Engineering to prepare it for machine learning tasks.
The dataset contains information about customers, demographics, product categories, and purchase behavior.

⚙️ Tools & Technologies

  • Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)
  • Jupyter Notebook
  • Feature Engineering

📊 Key Insights

  • Distribution of purchase amounts.
  • Impact of Gender and Age groups on spending.
  • Product categories with the highest sales.
  • Effect of occupation, city category, and stay duration on purchases.
  • Feature engineering applied to categorical variables for ML modeling.

📸 Visualizations

  • Purchase Distribution
    Purchase Distribution

  • Gender vs Purchase Behavior
    Gender vs Purchase

  • Age Group vs Purchase Behavior
    Age vs Purchase

🚀 How to Run

  1. Clone the repository 
    git clone https://github.com/YourUsername/Black-Friday-EDA.git
cd Black-Friday-EDA