🚀 Data Analysis Project: Exoplanets Dataset Analysis 🌌
In this project, I explore a dataset of exoplanets, planets outside our solar system, aiming to extract insights using data analysis techniques. The dataset contains information on 1013 exoplanets and their properties, including mass, radius, orbital period, orbital radius, and host star characteristics.
- How many planets are in the habitable zone?
- Is there a relationship between planet radius and star luminosity?
- Is there a relationship between planet mass and star mass?
- Is there a relationship between orbital period and star radius?
- data: Contains the dataset used in the analysis.
- notebooks: Jupyter Notebooks for data analysis and visualization.
- reports: Contains a detailed project report.
- Navigate to the notebooks folder.
- Run the Jupyter Notebooks for data analysis.
- Customize the analysis as needed for your exploration.
- Dataset units are relative to Earth or the Sun.
- Habitable Zone Distance criteria are applied for potential habitability.
- Estimated one planet per star in our galaxy.
🚀 Languages:
- Python
📊 Data Analysis and Visualization:
- Pandas: Data manipulation and analysis
- Matplotlib: Creating static, interactive, and animated visualizations
- Seaborn: Statistical data visualization
- NumPy: Numerical operations
🤖 Machine Learning:
- Scikit-Learn: Machine learning models and tools
📚 Other Tools and Frameworks:
- Jupyter Notebooks: Interactive computing and data exploration
🔧 Version Control:
- Git: Version control system
💻 Development Environment:
- Visual Studio Code
To deploy this project run
git clone https://github.com/ZahirAhmadChaudhry/Exoplanets-Dataset-Analysis.git
cd Exoplanets-Dataset-Analysis
pip install -r requirements.txt
Contributions are always welcome!
- Fork the repository.
- Create a new branch: git checkout -b feature-branch
- Make changes and commit: git commit -m "Description of changes"
- Push changes to your fork: git push origin feature-branch
- Create a pull request.
For a detailed report on the project, analysis, and conclusions, refer to the Project Report.
Feel free to explore, contribute, and use this project for your own analyses! 🚀✨
This project is licensed under the MIT License. See LICENSE for details.