TidyTuesday is a weekly social data project that provides real-world datasets for people to practice data analysis and visualization skills.
The project addresses the need for accessible, practice-oriented datasets by releasing a new dataset every Monday and inviting participants to explore it, create visualizations or analyses, and share their work with code. Participants can work with the data using R, Python, Julia, or other programming languages, and can produce outputs ranging from static visualizations to interactive Shiny apps or Quarto reports. The emphasis is on practicing data tidying and exploration techniques rather than drawing causal conclusions from the data.
TidyTuesday suits anyone learning data analysis, from students in formal courses to self-taught practitioners. The project is particularly valuable for those wanting structured, guided practice with real datasets in a supportive community context. It works well for educators looking to incorporate practical data work into curricula, as the datasets are curated specifically for learning purposes and come with clear participation guidelines. The project welcomes contributions from the community, including dataset submissions and improvements to make the project more accessible to users of different programming languages.
The project has expanded its educational reach, with surveys indicating adoption across numerous courses. Community participation in dataset curation has grown, with pull requests contributing new datasets, improvements for Python and Julia users, and other enhancements to the project infrastructure. The organizers have established concrete goals for improving dataset curation processes and tooling to support future growth.
