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06_Proptech

Jupyter notebook analyzing housing rental market data with interactive visualizations using PyViz, Plotly, and the Mapbox API.


Technologies

  • PyViz
  • The Mapbox API

Installation Instructions

Create a new conda environment to avoid conflicts with other package installations:

conda deactivate
conda update conda
conda create -n pyviz python=3.7 anaconda
conda activate pyviz

Install PyViz packages:

conda install -c plotly plotly=4.13.
conda install -c pyviz hvplot
  • PyViz require NodeJS version >= 12
conda install -c conda-forge nodejs=12

Install required JupyterLab Dependencies:

conda install -c conda-forge jupyterlab=2
jupyter labextension install jupyterlab-plotly@4.13.0 --no-build
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.13.0 --no-build
jupyter labextension install @pyviz/jupyterlab_pyviz --no-build
jupyter lab build

Install python-dotenv

pip install python-dotenv

Examples

Housing Units Sold by Year Average Sale Price per Sq Ft and Gross Rent Prices by Year by Neighborhood Mapbox Plot


Contributors

Starter code was given in the Rice FinTech Bootcamp and all modifications were made by Remy Dillenseger.


License

This project is licensed under the MIT License. Click Here for more information.

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Jupyter notebook analyzing housing rental market data with interactive visualizations using PyViz, Plotly, and the Mapbox API.

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