Welcome to our AriBnB reporting and analysis plattform! Great to have you here! With this short documentation we would like to give you some basic information about the goal of the app and why you should use it. So, let's get started.
It's holiday season! But wait, we still need to find a suitable and cheap accommodation. Where should we start? If this is your question, our AirBnB reporting and analysis tool can help you right away. In our app we try to provide you all relevant information you need to have to find the best and suitable accommadation on AirBnB for your next Holidays. How we try to achieve this goal
We know how hard and time intense it can be to find the right place to spend your holidays. Our goal is to make your life easier when it comes to your holidays. With a user friendly tool we want to achieve that everybody can find their favorite and the most suitable accommodation according to their needs. It should not matter if you are looking for the cheapest or most expensive one, with our tool you should be able to find whatever your are looking for.
We would like to introduce ourselves shortly. We are Viola Meier, Romano Brentani, Lukas Künzi, Barbara Dravec, four students currently doing their Bachelors degree in Computer Science at the University of Berne, Switzerland. You find more information about us in the members file. This application is being developed by our team within the Bachelor's program "Programming for Datascience" at University of Berne.
The project uses a rich dataset from Kaggel that contains extensive details about AirBnB's listings. The project emphasises interactive features. Users can analyse the data using parameters of their choice. For example, the AirBnB data can be analysed by city, neighbourhood or room type. An additional advantage of the reporting tool is the clear visualisation of the data, which makes the analysis understandable and intuitive.
To get started, clone the repository and run
pip install -r requirements.txt
Python version 3.12 or higher is required.
Before running the dashboard the first time, run the following command to preprocess the data:
python src/run_data_preprocessor.py
Only if the data/Airbnb_Open_Data.csv is updated, run this again.
To start the dashboard run
streamlit run src/home.py
If you are interested in working on the project and would like to contribute improvements or further ideas, please check out our ROADMAP.md file. To participate in the project, please get in touch with Romano Brentani: romano.brentani@students.unibe.ch
If you want to contact us regarding a project-related problem or an enhancement, you can create an issue in our GitHub repository. The option to create an issue will be available once we have set up the GitHub environment. For other questions or problems, please feel free to contact Romano Brentani: romano.brentani@students.unibe.ch
Thank you for your interest, for visiting this page, or for collaborating with us.
Our project is open source under the GNU General Public License v3.0. For further information and details consider the LICENSE.md file.