https://exomatch.streamlit.app/

Find Your Planet’s Cosmic Twin
exoMatch is a Streamlit app that lets you design a hypothetical planet and discover which known exoplanets are most similar — powered by NASA’s Exoplanet Archive data and our custom similarity + habitability scoring models.

• Interactive Input – Adjust key planetary features with intuitive sliders:

  • Radius (Earth radii)
  • Mass (Earth masses)
  • Equilibrium Temperature (K)
  • Orbital Period (days)

• Dynamic Visualization – A responsive planet graphic updates live:

  • Size = Radius
  • Core darkness = Mass
  • Color gradient = Temperature
  • Orbital speed lines = Orbital Period

• Smart Matching – Our backend models use KNN + clustering to:

  • Find the Top-5 most similar exoplanets to your design
  • Assign each a Habitability Score (0–1, higher = more Earth-like)

• Educational & Engaging – Makes raw exoplanet data accessible to everyone through an intuitive, space-themed interface.

├── app.py # Streamlit frontend ├── main.py # Backend entrypoint ├── knn_model.py # KNN similarity model ├── kmeans_model.py # KMeans clustering for habitability ├── habitability.py # Habitability scoring logic ├── planet_cluster_representatives.csv ├── PS_2025.09.20_19.26.05.csv # NASA Exoplanet Archive data ├── PS_top100_by_habitability.csv ├── PS_top100_by_knn_habitability.csv └── README.md

Clone the repo and install dependencies:

git clone https://github.com/manasv777/exoMatch.git cd exoMatch pip install -r requirements.txt Requirements: Python 3.10+ recommended. Streamlit, pandas, scikit-learn are required.

Usage Run the Streamlit app:

Copy code
streamlit run app.py
Then open the provided local URL in your browser.

Data Sources NASA Exoplanet Archive – Planetary Systems

Derived CSVs included in this repo (cleaned + feature-selected).

Hackathon Context exoMatch was built for the Carolina Data Challenge 2025 under the Natural Sciences track. Our goal: turn complex exoplanet datasets into an interactive tool that inspires curiosity about space exploration and highlights why studying exoplanets matters.

Future Work Expand feature set beyond 4 core parameters

Incorporate stellar properties into similarity scoring

Deploy as a public web app (e.g., Streamlit Cloud)

Team: Sai Yadavalli, Sidharth Yeramaddu, Dhanvi Movva, Manas Vellaturi