Code repository of team Null Pointer for SMU DataFest 2026.
Datafest-26/
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├── Analysis/ # Exploratory and feature analysis scripts
│ ├── Andrusha_Does_Stuff/ # Age, capacity, geography, and social analysis
│ ├── Hardness/ # Hardness scoring and interactive map app
│ ├── KansasMapApp/ # Kansas county-level map visualization
│ ├── Social Determinants/ # Social determinants by county
│ └── age_diagnosis_analysis.py
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├── Data Cleaning/ # Data preparation scripts and notebooks
│ ├── hospital_encounters.ipynb
│ ├── Encounters_Patients_Cleaner.ipynb
│ ├── ChronicDiagnosisCleaning.py
│ ├── extract_relevant_departments.py
│ └── is_chronic_encounters.py
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├── Monte Carlo & Super Learner/ # Optimization and ML modeling
│ ├── MonteCarloOptimalClinic.py # Monte Carlo clinic optimization
│ ├── 3D_MonteCarlo.py # 3D Monte Carlo simulation
│ ├── SL_Optimizer.py # Super Learner optimizer
│ └── hardness_config.toml
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├── Utilities/ # Shared utility modules
│ ├── ReturnFunctions.py # Data loading and cross-reference helpers
│ └── clinic_utils.py
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├── Documentation/ # Project documentation
├── outputs/ # Analysis results and CSVs
├── NullPointer_onepager.md # Project one-pager
├── NullPointer_slides.pdf # Presentation slides
└── README.md
- Utilities/ReturnFunctions.py — Core utility for loading and caching datasets with lazy loading
- Utilities/clinic_utils.py — Shared clinic-related helper functions
- Monte Carlo & Super Learner/MonteCarloOptimalClinic.py — Finds optimal clinic placement via Monte Carlo simulation
- Monte Carlo & Super Learner/SL_Optimizer.py — Super Learner-based optimization
- Analysis/Hardness/hardness_score.py — Computes hardness scores for geographic regions
- Analysis/Hardness/HardnessMapApp.py — Interactive map for hardness visualization
- Analysis/KansasMapApp/KansasMapApp.py — County-level Kansas map application