🌍 Global Power Plant Analysis

Welcome to the Global Power Plant Analysis repository! This project features a Streamlit-based interactive web app designed to explore and analyze worldwide energy generation data. With this tool, users can visualize and understand the intricacies of global energy production, making informed decisions based on comprehensive data analysis.

📚 Table of Contents

• Introduction
• Features
• Technologies Used
• Installation
• Usage
• Data Sources
• Contributing
• License
• Contact
• Releases

📝 Introduction

The Global Power Plant Analysis project aims to provide insights into the energy sector by utilizing an extensive database of power plants around the world. With energy demands rising globally, understanding energy generation patterns is crucial for sustainable development. This app allows users to explore various aspects of energy generation, including sources, capacities, and geographical distributions.

🚀 Features

• Interactive Visualizations: Explore data through various charts and graphs that highlight trends and patterns in energy generation.
• Data Filtering: Filter data based on different criteria such as country, energy source, and capacity.
• Comparative Analysis: Compare energy production across different regions and sources.
• Predictive Modeling: Use machine learning techniques to predict future energy generation trends based on historical data.
• User-Friendly Interface: A clean and intuitive design makes it easy for users of all skill levels to navigate the app.

🛠️ Technologies Used

This project leverages several technologies to deliver its functionality:

• Streamlit: A powerful framework for building web apps for data science.
• Pandas: A library for data manipulation and analysis.
• Matplotlib: A plotting library for creating static, animated, and interactive visualizations.
• Seaborn: A statistical data visualization library based on Matplotlib.
• Scikit-learn: A machine learning library for Python that provides tools for predictive modeling.
• Plotly: A graphing library that makes interactive, publication-quality graphs online.

💻 Installation

To get started with the Global Power Plant Analysis app, follow these steps:

1. Clone the repository:

   git clone https://github.com/FurkAlb/Global-Power-Plant-Analysis.git

2. Navigate to the project directory:

   cd Global-Power-Plant-Analysis

3. Install the required packages:

   pip install -r requirements.txt

🎉 Usage

To run the app, execute the following command in your terminal:

streamlit run app.py

This command will start a local server, and you can access the app in your web browser at http://localhost:8501.

📊 Data Sources

The data used in this project comes from various reliable sources, including:

• Global Energy Database: A comprehensive dataset that includes information on power plants worldwide.
• International Energy Agency (IEA): Provides statistics and reports on energy production and consumption globally.
• World Bank: Offers data on energy access and generation across different countries.

🤝 Contributing

We welcome contributions from the community! If you would like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/YourFeature

3. Make your changes and commit them:

   git commit -m "Add some feature"

4. Push to the branch:

   git push origin feature/YourFeature

5. Open a pull request.

Please ensure your code adheres to the project's coding standards and includes appropriate tests.

📄 License

This project is licensed under the MIT License. See the LICENSE file for more details.

📞 Contact

For any questions or suggestions, feel free to reach out:

• Author: Furkan Albayrak
• Email: furkan@example.com
• GitHub: FurkAlb

📥 Releases

To download the latest release of the app, please visit the Releases section. Here, you can find the most recent version of the app and any updates or fixes that have been made.

🌟 Conclusion

The Global Power Plant Analysis app serves as a valuable tool for anyone interested in understanding energy generation on a global scale. With its user-friendly interface and robust data analysis capabilities, it empowers users to make informed decisions in the energy sector. We encourage you to explore the app and contribute to its development.

Thank you for your interest in this project! We look forward to your feedback and contributions.