An interactive Shiny dashboard for analyzing U.S. office leasing trends and forecasting 2025 Q1 leasing activity using machine learning. This project was developed as part of the 2025 ASA DataFest at Penn State University, a national data science competition organized by the American Statistical Association.
To identify the most competitive and investment-ready U.S. cities in the post-COVID leasing market using trend scoring and forecasting models.
The dashboard includes four interactive pages:
- Home – Project overview and team
- Method – Data, feature engineering, and model methodology
- Market Overview – Heatmap and 3D trend score visualizations
- Trend Forecast – Leasing growth forecast for 2025 Q1
📁 Root Directory
│
├── 📂 docs/ # Project documentation and screenshots
│ └── page.png # Page-level screenshots
│
├── 📂 R/ # Custom R scripts used in data processing and modeling
│ ├── build_features.R # Feature engineering pipeline
│ ├── train_model.R # Model training and forecasting
│ └── trend_scoring.R # Market trend score calculation
│
├── app.R # Main Shiny app UI + server code
├── DESCRIPTION # App metadata (title, author, license, etc.)
├── CODEOWNERS # GitHub file to auto-assign code reviewers
├── .gitignore # Files and folders to ignore in version control
├── .lintr # Linting rules for R code style
- Data Period: 2021 Q4 to 2024 Q4
- Trend Score: Composite Z-score using rent, vacancy, occupancy, unemployment, and leased SF
- Model: XGBoost regression on lagged features
- Target: Forecast 2025 Q1 leased square footage
Due to data licensing agreements and privacy considerations, the original leasing dataset used in this project has been removed from the repository.
The app and code remain accessible for reference, but full functionality (e.g., trend scoring and forecasting) requires the proprietary source data, which is not publicly distributed.
If you are a competition judge, instructor, or reviewer seeking access, please contact the project team directly.
This repository was forked and adapted from the EducationShinyAppTeam/App_Template, originally created by the Education Shiny App Team for instructional and research use.
We thank the original authors for providing the structural foundation for our project.
This project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
Under the following terms:
- Attribution (BY): You must give appropriate credit and indicate if changes were made.
- NonCommercial (NC): You may not use the material for commercial purposes.
- ShareAlike (SA): If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
🔗 License details: https://creativecommons.org/licenses/by-nc-sa/4.0/