Project Name: Technical Systems Data Analysis in Buildings

This is a GitHub project that aims to analyze technical systems data in buildings, including HVAC systems, lighting systems, and energy consumption data. The project will focus on using Python programming language and relevant libraries to process, clean, and analyze data, as well as visualize the results.

Goals

The project goals are:

• To provide insights into the performance of technical systems in buildings and identify areas for improvement.
• To develop a reproducible data analysis workflow that can be applied to other buildings and technical systems.
• To explore correlations and patterns in the data to gain a deeper understanding of the performance of technical systems.

Data

The data used in this project will come from various sources, including building management systems (BMS), energy management systems (EMS), and other relevant sources. The data will be in different formats and may require preprocessing before analysis.

Tools and Libraries

The project will use Python programming language and relevant libraries for data analysis, including but not limited to:

• Pandas for data manipulation and cleaning.
• Matplotlib and Seaborn for data visualization.
• Scikit-learn for machine learning algorithms.
• Jupyter Notebook for data analysis and visualization.

Getting Started

To get started with the project, you will need to have Python and relevant libraries installed on your machine. You can clone the repository to your local machine and run the code in Jupyter Notebook.

git clone https://github.com/BrenEng/dataanalyse

Contributing

Contributions to this project are welcome. You can contribute by submitting bug reports, feature requests, or pull requests. Before contributing, please read the CONTRIBUTING.md file for more information.

License

This project is licensed under the MIT License.