Housing Price Prediction Dataset - Project Structure
RSK World - Free Programming Resources & Source Code
Website: https://rskworld.in
Contact: help@rskworld.in, support@rskworld.in
Phone: +91 93305 39277
Founder: Molla Samser
Designer & Tester: Rima Khatun
Created: 2026

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PROJECT FILES
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📁 Root Directory
├── 📄 housing_prices.csv                 - Main dataset (CSV format)
├── 📄 housing_prices.json                - Dataset (JSON format)
├── 📄 data_analysis.py                   - Basic data analysis and model training script
├── 📄 data_visualization.py              - Data visualization script
├── 📄 housing_price_prediction.ipynb     - Jupyter notebook for interactive analysis
├── 📄 validate_data.py                   - Data validation script
├── 📄 advanced_models.py                 - Advanced ML models (XGBoost, LightGBM, etc.) [NEW 2026]
├── 📄 feature_engineering.py             - Advanced feature engineering [NEW 2026]
├── 📄 hyperparameter_tuning.py           - Hyperparameter tuning with Grid/Randomized Search [NEW 2026]
├── 📄 model_comparison.py                - Model comparison and visualization [NEW 2026]
├── 📄 predict_price.py                   - Price prediction utility [NEW 2026]
├── 📄 requirements.txt                   - Python package dependencies
├── 📄 README.md                          - Project documentation
├── 📄 index.html                         - Demo web page
├── 📄 dataset_info.txt                   - Detailed dataset information
├── 📄 LICENSE.txt                        - License information
├── 📄 .gitignore                         - Git ignore rules
└── 📄 PROJECT_STRUCTURE.txt              - This file

📁 Generated Directories (created when running scripts)
├── 📁 plots/                             - Visualization output directory
├── 📁 models/                            - Saved trained models [NEW 2026]
├── 📁 tuned_models/                      - Hyperparameter-tuned models [NEW 2026]
└── 📁 housing_prices_engineered.csv      - Engineered dataset [NEW 2026]

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FILE DESCRIPTIONS
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housing_prices.csv
  - Primary dataset file in CSV format
  - Contains 50 property records with 20 features
  - Ready for pandas import

housing_prices.json
  - Dataset in JSON format
  - Alternative format for web applications
  - Contains same data as CSV

data_analysis.py
  - Python script for data analysis
  - Includes model training (Linear Regression)
  - Generates statistics and evaluation metrics

data_visualization.py
  - Python script for creating visualizations
  - Generates plots and saves to plots/ directory
  - Includes correlation heatmaps, distributions, scatter plots

housing_price_prediction.ipynb
  - Jupyter notebook for interactive analysis
  - Complete workflow from data loading to model evaluation
  - Includes both Linear Regression and Random Forest models

validate_data.py
  - Utility script to validate dataset files
  - Checks file integrity and structure
  - Verifies all required files exist

requirements.txt
  - List of Python packages needed
  - Use: pip install -r requirements.txt

README.md
  - Complete project documentation
  - Installation instructions
  - Usage examples

index.html
  - Demo web page
  - Showcases dataset features
  - Can be opened in browser

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QUICK START
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1. Install dependencies:
   pip install -r requirements.txt

2. Validate dataset:
   python validate_data.py

3. Run analysis:
   python data_analysis.py

4. Create visualizations:
   python data_visualization.py

5. Open Jupyter notebook:
   jupyter notebook housing_price_prediction.ipynb

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