This repo contains code for the Transport Data Science module at the Institute for Transport Studies, University of Leeds. See the website at https://itsleeds.github.io/tds/ and a summary of the catelogue entry at leeds.ac.uk

See the course website at itsleeds.github.io/tds

The quickest way to get started with the code for many people will be to use GitHub Codespaces. Click the Open in GitHub Codespaces button above to get started.

Alternatively you can launch this repository on Binder (notebooks).

If you’re using VS Code and have Docker installed you can open the project in a Devcontainer by pressing Ctrl+Shift+P, typing in “Devcontainer”, and selecting “Remote-Containers: Reopen in Container”.

We welcome contributions!

To fork and clone the repo, use the following commands:

# install the gh command line tool: https://cli.github.com/
gh repo fork itsleeds/tds
git clone tds
code tds # to open in VS Code, or open in your preferred editor
# make changes
git add .
git status # to check what you've changed
git commit -m "your message"
git push
gh pr create # to create a pull request

Please create an issue before contributing, so we can discuss the changes you’d like to make.

You can create and work on an issue with the following commands:

gh repo clone itsleeds/tds
cd tds # or code tds to open with VS Code
gh issue create # to create an issue
gh issue develop 123 --checkout # to create a branch and start working on issue 123
# make changes
git add .
git commit -m "your message"
git push
gh pr create # to create a pull request

The most reliable way to reproduce the website locally is using Pixi. It handles both R and Python dependencies in a single isolated environment.

1. Install Pixi: Follow the instructions at pixi.sh.
2. Initialize Environment:

   pixi install

3. Preview the website:

   pixi run preview

To reproduce the website using R, you can use the following command:

if (!requireNamespace("pak", quietly = TRUE)) {
  install.packages("pak")
}
pak::pak("itsleeds/tds")

Note for Python users: If your local machine lacks Python or the required libraries (like jupyter and geopandas), Quarto may fail to render documents containing Python code. We recommend the Pixi approach above to ensure all dependencies are met.

If you are on Windows, we strongly recommend using Pixi or GitHub Codespaces. If you prefer a manual setup, ensure you have:

1. Quarto installed.
2. R and Python installed and added to your PATH.
3. Python dependencies installed via: pip install jupyter jupyter-cache geopandas matplotlib shapely seaborn ipykernel osmnx.

See an archived version of the repo, before we switched to using Quarto, at https://github.com/itsleeds/tdsarchive

usethis::use_description()
usethis::use_package("stats19")
usethis::use_package("DT")
usethis::use_package("quarto")
usethis::use_package("zonebuilder")

wget https://github.com/citation-style-language/styles/raw/refs/heads/master/elsevier-harvard.csl