Teaching data science with puzzles

Of the many coding puzzles on the web, few focus on the programming skills needed for handling untidy data. During my summer internship at RStudio, I worked with Jenny Bryan to develop...

rstudio::conf 2019

Teaching data science with puzzles

January 25, 2019

Of the many coding puzzles on the web, few focus on the programming skills needed for handling untidy data. During my summer internship at RStudio, I worked with Jenny Bryan to develop a series of data science puzzles known as the "Tidies of March." These puzzles isolate data wrangling tasks into bite-sized pieces to nurture core data science skills such as importing, reshaping, and summarizing data. We also provide access to puzzles and puzzle data directly in R through an accompanying Tidies of March package. I will show how this package models best practices for both data wrangling and project management.

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About the speaker

Irene Steves

Irene holds an M.Sc. in Ecology and a B.A. in Integrative Biology, through which she first discovered R and data science. Her interest in data led her to the Arctic Data Center at the University of California Santa Barbara, a summer internship at RStudio, and ultimately to the Research & Data Science department at Riskified, where she now explores the complex patterns of fraud in eCommerce. In her free time, she studies Hebrew through podcasts and dubbed kids’ movies.