Proptech Analyzer
Proptech, the application of technology to real-estate markets, is an innovative domain in the fintech industry. Assume that you’re an analyst at a proptech company that wants to offer an instant, one-click service for people to buy properties and then rent them. The company wants to have a trial of this offering in the San Francisco real-estate market. If the service proves popular, they can then expand to other markets.
The python based program is built to assist a Proptech sales data analyst in using data visualization skills, including aggregation, interactive visualizations, and geospatial analysis, to find properties in the San Francisco market that are viable investment opportunities.
Technologies
This project leverages python 3.7.* with the following additional packages:
- Jupyter Notebook - The main module of the Financial Planner is written in Jupyter Notebook.
- Conda - Conda environment is recommended to have Pandas library and other dependencies pre-installed.
Required Libraries:
You may need the following libraries to work with the program.
- Pandas - pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive.
- hvPlot - hvPlot provides a high-level plotting API built on HoloViews that provides a general and consistent API for plotting data in Python.
Usage
To use the Proptech Analyzer application, clone the repository and run the san_francisco_housing.ipynb with Jupyter notebook.
From the Git Bash terminal, make sure to 'activate conda' and appropriate virtual enivorment. Next, launch the JupyterLab web-based interactive development environment (IDE) interface by typing at the prompt:
> jupyter labThen, browse to san_francisco_housing.ipynb starter code file to run the program. See the image below for a quick hint.
Contributors
FinTech Labs, Inc.
License
None