Contributors: Sid Kapur, Zack Subin
The goal of this project is to produce (1) a Python library for loading data from the US Census Building Permits Survey as a pandas DataFrame, and (2) a Plotly/Dash webapp that displays this data in an interactive way so that people can explore this data in more detail.
This project assumes that you have pipenv installed. To create the virtualenv and install the packages, just run pipenv install from the root directory.
When adding/updating packages, you'll want to commit both Pipfile and Pipfile.lock to the repo, to make sure that everyone is using the same versions of each package.
There's a sample notebook that shows you how to use the library in permitting data.ipynb. I recommend playing with it using JupyterLab, which you can start by running pipenv run jupyter lab.
Plotly Dash is supposedly "the most popular framework for building ML and data science apps", so that sounds like a good thing to use for the visualization.
Since this is a Python webapp, we'll have to use Heroku to host the Python server. Fortunately, Dash has specific documentation for how to use Dash with Flask and Heroku, so hopefully this will be pretty easy to set up.
For CSS stuff, I like to use tailwindcss, but I'm hoping that Dash will take care of most of it so that we don't need to mess with CSS too much.
Once I get the Heroku account set up, I'll post the live URL and the instructions for pushing to Heroku here!