The Airbnb Analysis Project seeks to optimize property listings and enhance user experiences by analyzing data on trends, preferences, and pricing dynamics. With a focus on data science, the project aims to provide valuable insights for hosts and improve booking satisfaction for guests. The ultimate vision is to create a comprehensive solution benefiting both hosts and guests in the Airbnb ecosystem.
Explain where you obtained the data, whether it's publicly available or proprietary. Include any relevant links or references.
Provide a description of the data structure, including key fields and their meanings. If possible, include an example document from the MongoDB collection.
Describe the main components of the project, including data retrieval, data cleaning, web application development, analysis, and visualization.
List the skills demonstrated in this project, such as Python scripting, data preprocessing, MongoDB, Streamlit, data visualization, etc.
Provide instructions on how to run the project locally. Include any necessary setup steps, dependencies, and configuration.
Include screenshots or GIFs that showcase the project's web application, interactive visualizations, or key findings.
Explain the organization of project files and directories. Provide a brief overview of each major folder and its contents.
List the main libraries and tools used in the project, along with their versions. Include a requirements.txt file for easy installation.
List the project contributors with their names and contact information (if desired).
Specify the project's license, if applicable.
Give credit to any sources, libraries, or tutorials that influenced or supported your project.
Discuss potential improvements or additions to the project in the future. This could include feature enhancements, data updates, or scalability considerations
Encourage users and contributors to provide feedback or report issues. Include contact information or a link to the project's issue tracker.
Summarize the project's achievements and key takeaways. Mention any challenges faced and lessons learned during the project.