🪐 Exoplanet Discovery Timeline & ESI Calculator

Interactive data visualization project that analyzes NASA's exoplanet archive to identify potentially habitable worlds using the Earth Similarity Index (ESI).

📊 Overview

This project combines Data Science with Web Visualization to explore the history of exoplanet discoveries.

• Data Processing: Python scripts ingest raw NASA data, cleaning and filtering candidates.
• Math Modeling: Calculates the Earth Similarity Index based on planetary radius, density, escape velocity, and surface temperature.
• Visualization: An interactive D3.js/JS timeline allowing users to explore the universe's candidates.

🧮 The Math: Earth Similarity Index (ESI)

The core of the analysis is the ESI formula, implemented in Python:

$$ESI = \prod_{i=1}^{n} \left(1 - \left| \frac{x_i - x_{i0}}{x_i + x_{i0}} \right| \right)^{\frac{w_i}{n}}$$

(See compute_esi.py for implementation details)

🛠️ Tech Stack

• Backend / Processing: Python 3, Pandas, NumPy, Flask.
• Frontend: HTML5, CSS3, Vanilla JavaScript.
• Data Source: NASA Exoplanet Archive.

🚀 How to Run Locally

1. Clone the repository:

   git clone [https://github.com/alvarorm3008/VISUALIZATION-UIB.git](https://github.com/alvarorm3008/Exoplanet-Visualization.git)
   cd Exoplanet-Visualization

2. Set up the environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

3. Launch the Visualization:

   python serving_archivos.py

   Open your browser at http://127.0.0.1:5000/timeline.html

---

Author: Alvaro Rodriguez and Agustin Soares