fortune-uwha/python-panel-dashboard-airbnb

Data visualization dashboard in Python from Jupyter Notebook using Open source visualisation tool Panel

Airbnb Data Analytics/Visualisation Project: A Python-Panel Dashboard🗽

An interactive dashboard in Python from Jupyter Notebook using Open source visualisation tool Panel

Table of Contents

• Project Overview
• Getting Started
• Dependencies
• Data
• Dashboard
• Usage
• Acknowledgement
• Contributing
• License

Project Overview📖

The goal of this project is to provide insights and visualizations based on the Airbnb data in New York City. It includes interactive charts and filters to explore different aspects of the data, such as pricing trends, neighborhood comparisons, and room types.

Getting Started🦘

To get started with the project, follow these steps:

1. Clone the repository to your local machine.
2. Install the required dependencies (see the Dependencies section for details).
3. Get the Airbnb dataset for New York City (see the Data section for details).
4. Run the project script or notebook to generate visualizations and explore the data.

Dependencies

The project relies on the following dependencies:

• Python 3
• Pandas
• Panel
• HvPlot

To install the dependencies, please refer to the requirements.txt file

Data

The Airbnb dataset used in this projectis gotten from kaggle. It includes information about Airbnb listings in New York City. You can get the dataset here.

Once you have the dataset, update the file path in the project script or notebook accordingly.

Dashboard

Sketch of Airbnb Visualisation:

Result⭐:

Usage

To use the project, follow these steps:

1. Ensure you have the required dependencies installed (see the Dependencies section).
2. Make sure you have obtained the Airbnb dataset (see the Data section).
3. Run the project script or notebook using Python.
4. Explore the visualizations and interact with the filters to analyze different aspects of the Airbnb data.
5. To serve the dashboard locally, use the command:

panel serve airbnb.ipynb

Acknowledgement

This project was inspired by the work and ideas of Thu-Vu92

Contributing

Contributions to this project are welcome! If you find any issues or have suggestions for improvements, feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License.