science

TidyTuesday

TidyTuesday is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand TidyTuesday rather than just read about it. In short: TidyTuesday, also noted as Tidy Tuesday, tidytuesday, or #tidytuesday, is a weekly community of practice that is currently organized by the Data Science Learning Community (DSLC). A new data set is highlighted each week for participants to practice exploring, visualizing, and sharing findings.

Key takeaways

TidyTuesday belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect TidyTuesday to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of TidyTuesday from memory before moving on to harder problems.

Reference excerpt

TidyTuesday, also noted as Tidy Tuesday, tidytuesday, or #tidytuesday, is a weekly community of practice that is currently organized by the Data Science Learning Community (DSLC). A new data set is highlighted each week for participants to practice exploring, visualizing, and sharing findings. Participants can follow the daily hashtag #tidytuesday on social media.

History

TidyTuesday was started by Tom Mock, a product manager at Posit PBC, on April 1, 2018. The motivations to create this was for newcomers to data and more experienced data scientists to feel less socially isolated and a means to practice skills like acquiring, cleaning, wrangling, visualizing and presenting data. Some participants have shared feeling inspired by others' data visualizations and noting that most people will share their code in order to replicate their work.

Impact TidyTuesday has also been used by other groups or features published data. R-Ladies Global have used TidyTuesday datasets as a hackathon to practice data skills. In February 2021, Allen Hillery, Athony Starks, and Sekou Tyler, started the #DuboisChallenge. This challenge had participants use modern data visualization tools to recreate the data visualizations by sociologist and activist W.E.B.Du Bois. Then in 2021 and 2022, TidyTuesday highlighted these datasets for the data community. In 2021, TidyTuesday featured the zipcodeR dataset that contains 41,000 ZIP codes for analysis.

Educators training data scientists have struggled to coordinate their preparation, but some have suggested to create a portfolio to have highlight technical skills and data thinking skills. TidyTuesday is one suggested way to find datasets to create a formal, visual project. This can be a means to help teach novice data practitioners on how to better program in programming languages like the R programming language.

Illustrations

TidyTuesday logo

Worked examples

Example 1 — a first encounter with TidyTuesday

Start with the simplest possible case. Write down what TidyTuesday claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to TidyTuesday before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about TidyTuesday ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of TidyTuesday

In research: TidyTuesday appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses TidyTuesday in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: TidyTuesday is common in secondary-school and first-year university syllabi. It links to neighbouring topics Data and information visualization, Data science, R (programming language), so understanding it makes those chapters shorter.
In everyday life: Look for TidyTuesday outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study TidyTuesday in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what TidyTuesday means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain TidyTuesday out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is TidyTuesday in simple terms?

Why does TidyTuesday matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study TidyTuesday?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on TidyTuesday.