Requirements.txt

Requirements for Black Friday Sales Analysis  

1. Dataset:  
   - Sales transaction data, including customer demographics (age, gender, marital status), products purchased, and purchase amounts.  
   - Data fields like product categories, city tier, and occupation are essential for deeper insights.  

2. Software and Tools:  
   - Python: Programming language for data analysis.  
   - Libraries:
     - Pandas: Data cleaning and manipulation.  
     - NumPy: Numerical computations.  
     - Matplotlib/Seaborn: Data visualization.  
     - Scikit-learn: For advanced analysis or predictive modeling (if needed).  
     - Jupyter Notebook: For interactive analysis and visualization.  

3. Environment Setup:  
   - Python 3.x installed.  
   - Virtual environment or dependency management tools like `pip` or `conda`.  

4. Data Preprocessing :  
   - Cleaning: Handle missing or inconsistent values.  
   - Transformation: Convert categorical data to a usable format.  
   - Aggregation: Combine or summarize data based on relevant features.  

5. Skills :  
   - Knowledge of data preprocessing and wrangling.  
   - Experience with data visualization techniques.  
   - Understanding of basic statistics for interpreting trends and insights.  

6. Objectives :  
   - Analyze trends by age, gender, marital status, and occupation.  
   - Identify high-performing products and customer segments.  
   - Derive actionable insights for strategic decision-making.  

This setup ensures a comprehensive and effective analysis of Black Friday sales data.