This application uses aggregation, interactive visualizations, and geospatial analysis to find properties in the San Francisco market that are viable investment opportunities.
- Python interpreter v3.9.12
- Pandas library: Data analysis and manipulation tools
- Python sys library: Support for system-specific parameters and functions
- Python dotenv library: Support for using secure environment variables
- Python hvplot library: Support for interactive plotting
- Python Geoviews library: Support for plotting geographic data on a map interface
To use this housing analysis application simply clone the repository and open the san_francisco_housing.ipynb script in the Jupyter Lab application.
san_francisco_housing.ipynb
The source code for the application is licensed under the MIT license, which you can find in the LICENSE file in this repo.