Formula uOttawa's Data Analysis Tool

What this project is

This repository contains a custom analysis toolkit that connects to the team’s data sources to generate reusable plots, metrics, and reports tailored to FSAE needs. It is designed to be lightweight and easy for team members to run, modify, and extend as the car and sensors evolve over the season.

​ Why build our own tools

Off‑the‑shelf software that integrates with the ECU and dash (such as RaceStudio3) is powerful, but it hides much of the implementation and limits how deeply the team can experiment with custom analysis workflows. Building an in‑house toolkit aligns with the core FSAE goal of learning how systems work by designing and implementing them, rather than only configuring commercial solutions.

​ Learning focus for new members

This project is also a training ground for new software sub‑team members to learn modern software development practices in the context of real telemetry and performance questions. Contributors gain experience in data engineering, numerical analysis, and visualization while shipping tools that the rest of the team uses on a regular basis. ​

Videos to get started

Race Telemetry for driver performance

Data Analysis in Racestudio3

Formula SAE design competition format

License

Copyright (c) 2025 Formula uOttawa Contributors.

This project is licensed under the MIT License - see the LICENSE file for details.

Setup

First, download and install the Anaconda installer, this will allow you to organize the libraries we use. Then, open Anaconda prompt (as administrator) and set up a new environment with the following command:

conda create --name FSAEDataGUI python=3.8

Then, activate the environment using:

conda activate FSAEDataGUI

Once activated, you can begin installing the necessary libraries using:

conda install [libraryName] and pip install [libraryName]

List of libraries:

• dearpygui (pip)
• numpy (conda)
• pandas (conda)
• scipy (pip)

Then, verify your dearpygui installation by running the following command:

python -m dearpygui.demo

You should see a demo program showing off the features. You can now install Git and your preferred integrated development environment (IDE) to contribute to the software! Make sure to set your environment to FSAEDataGUI in the IDE. You should also be familiar with using branches and making pull requests on Git, you can find many good tutorials on YouTube. We recommend using GitHub Desktop and VSCode.

Ongoing projects:

• Data analysis tool
  • Data loading
  • Data pre-processing
  • Main GUI and UX
  • File annotation and management system
• LLM chat bot
• Automatic SharePoint physical backup
• Data inspection tool