PandeMap

Map data
Implementation A - pre-pandemic
Implementation B - post-pandemic

Inspiration

Over the last 2 years of pandemic, we've seen some of our favourite businesses temporarily, or permanently close (R.I.P. La Récreation). As geography nerds, we wanted to investigate this using MAPS!

What it does

A simple web app provides a blank map of Montreal's greater urban area. Users can then select what types of buildings they would like to analyze on the dynamic map (e.g. pharmacies, grocery stores, restaurants). Coloured points will appear on the map corresponding to each building type, as well as a toggle button, allowing you to compare the layout of the selected businesses pre- and post-pandemic.

How we built it

This project is powered using OpenStreetMap, a crowdfunded map of the world! We captured OSM data of selected building types in two snapshots - one from before COVID (February 2020) and one at the time of the project (January 2022). Using Python, and specifically the pyrosm package, we formatted the data into a version that can be analyzed by Python. From there, we read the user input based on frontend filter selection and generate an image from the requested map data (in the form of a Matplotlib graph). Finally, the custom map is displayed on the user interface via a Flask web app.

Challenges we ran into

Pyrosm is an obscure package with obscure dependencies that does not have a robust history of installations and troubleshooting like other packages. Therefore, it took more time than we care to admit to get the package working locally.