In this episode, I chat with Nick Tierney, a statistician, data scientist, and creator of the {naniar} R package for exploring missing data. Nick reflects on his journey from a psychology undergrad to a PhD in statistics, and how open-source tools—and a deeply curious mindset—shaped his path.

We discuss Nick’s early struggles with R, the importance of community, and his evolution into package development and consulting. He also walks through the why and how of testing R packages, making the case for better, more reliable code.

Resources mentioned:

• {naniar} package

• Books: (1) The R Book by Michael Crawley, and (2) R Packages by Hadley Wickham and Jenny Bryan

Connect with Garrick on Bluesky and GitHub

In this episode I sit down with Garrick Aden-Buie, a senior software engineer at Posit (formerly RStudio), to explore his latest project: brand.yml. This innovative tool aims to simplify and unify branding across various data science outputs, including Quarto documents, Shiny apps, and more.

Garrick shares the inspiration behind brand.yml, stemming from his experiences in creating custom theming solutions at different organizations. Recognizing the repetitive nature of this task, he developed brand.yml to serve as a single source of truth for styling, enabling consistent application of brand guidelines across multiple platforms.

Important resources mentioned:

• brand.yml project page
• GitHub repo
• BSLib article on unified theming
• Blog post ‘Unified branding across Posit tools with brand.yml’ by Sarah Altman

Connect with Garrick on LinkedIn, Bluesky and Mastodon. Visit his Website to learn more.

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In this episode, I sit down with Robert Smith, co-founder of Dark Peak Analytics, to discuss his journey from academia to advising the UK government during the COVID-19 pandemic. Rob shares his experience building data models that directly influenced public health policy and decision-making at the highest levels. We also dive into his work with Parkrun, a community-driven initiative promoting equitable access to physical activity, and how he used R to analyze participation patterns and improve accessibility.

Rob's insights into health economics, simulation modeling, and the challenges of transitioning industries provide valuable lessons for data professionals.

Important resources mentioned:

• Dark Peak Analytics
• Academic Papers:
  https://wellcomeopenresearch.org/articles/5-9
  https://www.sciencedirect.com/science/article/pii/S0033350620304066
  https://www.sciencedirect.com/science/article/pii/S1353829221001222
  https://link.springer.com/article/10.1186/s12889-024-20420-0
  https://www.medrxiv.org/content/10.1101/19004143v1.full.pdf
• Map: https://iolmap.shinyapps.io/parkrun/
• Parkrun

Connect with Robert on:

LinkedIn: Robert Smith 

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 In this episode, I chat with Simon Couch, a software engineer at Posit, about his work on AI-powered R packages. Simon maintains open-source statistical software and explores how AI can streamline coding workflows. We discuss his journey from statistics and sociology to AI-driven tooling, his development of the PAL and Gander packages, and why AI won’t replace coding anytime soon—but can definitely make it easier. 

Improtant resources mentioned:

• Simon’s blog
• Tidyverse blog post on PAL & Gander

Connect with Simon on: 
LinkedIn: Simon P. Couch
Bluesky: @simonpcouch.com
Mastodon: @[email protected]
X: @simonpcouch‬

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In this episode, I chat with Terence Teo, Professor at Seton Hall University and expert in creating stunning 3D maps using the {rayshader} package in R. Terence discusses his journey into data visualization, specifically his use of R and the RayShader package to create mesmerizing 3D maps. Terence shares insights from his academic background in political science, his creative process for making maps, and how he balances artistic flair with technical rigor. The discussion dives into geospatial data, the intricacies of the {rayshader} and {rayrender} packages, and the value of experimentation in visual storytelling.

Important resources mentioned:

• River Basins of the Iberian Peninsula: https://bsky.app/profile/tterence.bsky.social/post/3kdbsv4bbc32k
• GitHub repo of code used

Connect with Terence on:  

• X: @researchremora
• Bluesky: @tterence.bsky.social‬

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In this episode, I chat with Alex Gold, who leads solution engineering and support teams at Posit. We talk about his new book ‘DevOps for Data Science’, and explore why DevOps principles are crucial for data scientists, even if you aren't working in hardcore production environments. Alex shares insights on how to think about putting your data science projects into "production"—whether it's a report for colleagues or a full-scale deployment. We discuss practical tips like using {renv} to manage package versions and ensure reproducibility, and Alex gives a live demo on setting it up in an R project. Tune in for key takeaways on making your data science work more robust, shareable, and ready for production.

Important resources mentioned:

• DevOps for Data Science: Buy the book here at 20% off using the discount code AFLY04. Check out the Github repo if interested.

Connect with Alex on:  

• X: @alexkgold
• LinkedIn: Alex Gold
• His website (alexkgold.space), where he occasionally blogs about data, management, and leadership.

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In this episode, I talk with Cédric Viddone, an Information Management Officer at UNHCR with over 15 years of experience in humanitarian data visualization. Cédric shares his journey from GIS and cartography to creating impactful infographics and embracing the R programming language. He discusses how R has revolutionized data efficiency within UNHCR, where it aids in producing faster, reproducible data products essential for crisis response. Cedric also highlights the growth of the UNHCR R community and introduces the organization's data visualization guidelines platform, which includes a custom ggplot theme that streamlines UNHCR branding. Additionally, Cédric explores the advantages of Quarto for developing UNHCR-branded templates, enabling team members to create consistent, polished reports with ease.

Important resources mentioned: 

• UNHCR data visualization platform
• UNHCR branded theme for ggplot2 and data visualization color palettes
• UNHCR Quarto revealjs extension
• UNHCR data viz GitHub repo

Connect with Cédric on:

• X: @cvidonne
• Mastodon: @[email protected]
• LinkedIn: Cédric Viddone

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In this episode, I talk with Christine Parker, the Senior GIS Analyst on the Community Broadband Networks team at the Institute for Local Self Reliance. Christine shares how she used R to clean, combine, and summarize data for a dashboard tracking enrollment in the Affordable Connectivity Program (ACP), a COVID-era initiative to help people access affordable internet. The dashboard gained wide attention. It was shared in advocacy circles, referenced in Congress, and discussed with the White House. Christine highlights R's value for performing repeatable data tasks, particularly with regularly updated datasets, and its advantages compared to manual Excel processes.

Important resources mentioned:

• The ACP dashboard 
• Code that Christine used to create the dashboard

Connect with Christine on:  

• X: @birdwrangler
• LinkedIn: Christine Parker, PhD

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In this episode, I chat with Crystal Lewis about data management and her recently published book titled ‘Data Management in Large-Scale Education Research’. Crystal, a freelance research data management consultant, shares insights on good planning and systematic implementation of practices that are key to effective data management. She discusses the importance of automated data validation, and outlines a structured approach to data cleaning. Additionally, Crystal reflects on her experience writing an open-source book with Bookdown and navigating the publishing process. 

Important resources mentioned:

• Crystal’s book Data Management in Large-Scale Education Research

Learn more about Crystal Lewis by visiting her website and connect with her on X (@Cghlewis), LinkedIn, GitHub, and Fosstodon.

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In this episode, I speak with Miles McBain, a data scientist and R package developer from Brisbane, Australia, about patterns and anti-patterns in data analysis reuse. Miles shares his journey from a generalist software developer to a data science specialist, his passion for R, and the evolution of his coding practices. We delve into the intricacies of code reuse in data analysis, discussing common pitfalls to avoid, the benefits of creating reusable code packages, the process of breaking down large codebases, and how teams can evolve their coding practices to enhance efficiency and maintainability.

Important resources mentioned:

• Patterns and anti-patterns of data analysis reuse blog post by Miles McBain
• Jenny Bryan’s talk ‘Code smells and feels’ presented during useR!2018

Connect with Miles McBain:

• Website: milesmcbain.xyz/
• GitHub: @milesmcbain
• Mastodon: https://fosstodon.org/@milesmcbain

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