Making Toronto's democracy more accessible.
-
Updated
Jun 10, 2026 - TypeScript
Making Toronto's democracy more accessible.
Data scraped from various sites for housing data around the greater Toronto area (GTA). Scrapes happen daily and data is in both JSON and CSV formats. Free to use for analysis.
Bike Share Toronto 2021 Data Analysis & Interactive Visualization
A UI for the myttc.ca API, made with tailwind and jquery.
Working repository for the study of the "Motor Vehicle Collisions Involving Killed or Seriously Injured Persons" database from Toronto Open Data.
Project Explores Toronto Neighborhoods and Housing using a variety of data science and machine learning techniques.
A prepared environment for beginners to start on data science(Python, Jupyter and Pandas), with code retrieving real time Covid-19 case open data, and sample plotting scripts.
Toronto bike share API library
An analysis of Toronto Paramedic Services' response times to determine its efficacy as an emergency service.
🚗 TorontoParking: Revolutionizing 🌆 Toronto's parking game! Tap into open data, find
Production-grade real-time transit analytics platform for Toronto TTC. Ingests GTFS Realtime feeds (vehicle positions & trip updates) every 30s, implements medallion architecture with MinIO data lake and Postgres warehouse. Airflow orchestration, Docker deployment. Built for analyzing delays, vehicle utilization, and service patterns.
Maze is an Android app (Android Auto compatible) that helps drivers avoid parking violations in real time. Drive with Waze 👻, Park with Maze 🚔
Working repository for CrashPoint ETL, a pipeline for processing and analyzing traffic collisions involving killed or seriously injured (KSI) persons from the City of Toronto
Statistical and geospatial analysis of Toronto Bike Share data and what it can tell us about the impact of changes to Toronto's bicycle infrastructure
This analysis looks at basement flooding and sewage service requests across Toronto wards from 2005 to 2023.
Identified trends in Major Crime Indicators data to recommend crime reduction strategies.
This is a repository for a research article published in the Journal of Responsible Technology (Elsevier). The article uses Machine Learning and Generative AI to compare how both technologies achieve a particular result in crime suspects exercises.
Geospatial dataset of 1000+ aggregated variables for neighbourhoods in Toronto, ON, CA
aws lambda function to get collection schedule for a Toronto address
Add a description, image, and links to the toronto-open-data topic page so that developers can more easily learn about it.
To associate your repository with the toronto-open-data topic, visit your repo's landing page and select "manage topics."