Resources

Technology resources

Software

• RStudio Cloud: https://rstudio.cloud/

• EDINA (https://noteable.edina.ac.uk/launch) for access to R and Python

• Python via different platforms; Google Colab, Jupyter notebook or you can install local platforms such as Anaconda.

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Code repository, version control, and collaboration

• GitHub: https://www.github.com

• GitLab: https://about.gitlab.com

• Happy Git with R: https://happygitwithr.com/

For the installation of related tools, you can follow the instructions available for R and RStudio for Github.

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Interactive visualisations and dashboards

• Shiny:

  • All things Shiny: https://shiny.rstudio.com/ (including a sample COVID-19 dashboard)
  • Deploy Shiny app on shinyapps.io: https://docs.rstudio.com/shinyapps.io/getting-started.html
  • Shiny tutorial (video): https://shiny.rstudio.com/tutorial/
  • Shiny tutorial (slides): https://rstudio-education.github.io/shiny-jsm18/

• Tableau:

  • Tableau Public: https://public.tableau.com/s/
  • Tableau Desktop - free student license: https://www.tableau.com/academic
    

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More resources

Some other suggested sources are listed below (not an exhaustive one);

• RStudio - Posit Sources: https://posit.co/resources/

• R related cheat-sheets: https://posit.co/resources/cheatsheets/

• UoE Introduction to Data Science course materials: https://uoe-ids.netlify.app/

• Centre for Data, Culture, and Society training courses: https://github.com/DCS-training

• Duke’s Center for Data and Visualization Sciences workshop materials: https://dukestatsci.github.io/datafest/workshops.html

• Google Colab resources: https://colab.google/resources/

• Jupyter resources: https://docs.jupyter.org/en/latest/