🛍️ Black Friday Sales EDA Project

📌 Project Overview

This project performs Exploratory Data Analysis (EDA) on Black Friday sales data to uncover purchasing patterns, trends, and insights. The goal is to analyze customer demographics, product categories, and purchase behavior using Python and visualization tools.

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🛠️ Tools & Technologies

• Python (Pandas, NumPy)
• Data Visualization: Matplotlib, Seaborn
• Google Colab Notebook

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📂 Project Workflow

1. Data Cleaning – Handled missing values, corrected data types, and removed duplicates.
2. Feature Analysis – Examined key features like Product Category, Purchase Amount, and Customer Demographics.
3. Visualization – Created plots to identify trends, patterns, and correlations.
4. Insights – Derived actionable conclusions to understand sales behavior.

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🚀 Key Learnings

• Clean and preprocess real-world retail datasets.
• Perform exploratory analysis to identify trends and correlations.
• Visualize data effectively to communicate insights.
• Understand customer behavior and purchase patterns.

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📖 How to Use

1. Open the notebook in Google Colab.
2. Run all the cells to replicate the analysis.
3. Modify or extend the analysis to explore additional insights.

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👩‍💻 Author

Shreya Chatterjee
Applied Statistics & Analytics | Aspiring Data Analyst | Business Analyst | Data Scientist | Consultant
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