Software by Jenny Bryan#
Posts and resources by Jenny Bryan#
Laboratory science to data science & the art of the growth gig | Lisa Elkin | Data Science Hangout
ADD THE DATA SCIENCE HANGOUT TO YOUR CALENDAR HERE: https://pos.it/dsh - All are welcome! We’d love to see you!
We were recently joined by Lisa Elkin, Senior Principal Computational Toxicologist at Pfizer, to chat about her career transition from a lab scientist to a data scientist, building Shiny apps for scientific audiences, and the value of internal programs for up-skilling and data literacy.
In this Hangout, we explore how to foster data science skills and build communities within a large organization. Lisa shares her experience with programs like an “Analytics Exchange,” where employees could dedicate 20% of their time to working on data science projects from across the company, allowing them to learn by doing. She provides tips on how to propose similar “growth gig” opportunities to leadership, highlighting the value of up-skilling the entire department to increase efficiency and innovation without necessarily hiring more specialists.
Lisa also gives advice for starting a new internal community from the ground up, emphasizing the need for a few passionate individuals and the importance of repeating introductory sessions to support newcomers. Lisa runs a Data Science Hangout internally at Pfizer!!
Resources mentioned in the video and zoom chat: Mastering Shiny Book → https://mastering-shiny.org/ Jenny Bryan - Code Smells and Feels Talk → https://github.com/jennybc/code-smells-and-feels Posit Academy → https://posit.co/products/enterprise/academy/
If you didn’t join live, one great discussion you missed from the zoom chat was about what a “mainframe” computer is. The conversation sparked memories of punch cards, floppy disks, and how the cloud is in some ways a return to the mainframe paradigm. Let us know below if you’d like to hear more about it! Better yet, join us live on Thursdays :) pos.it/dsh
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Thanks for hanging out with us!
Timestamps 00:00 Introduction 04:50 “What is toxicology?” 06:19 “What are the data types that your tool users are interfacing with?” 07:19 “What is an assay?” 08:15 “How does your science background benefit or disadvantage you as a data scientist?” 14:55 “What kind of audience do you build Shiny apps for and what is your workflow?” 18:05 “What made you decide to switch to industry and what were the bottlenecks between academia and industry?” 24:39 “Do you have any tips on proposing an ‘analytics exchange’ program to leadership?” 28:38 “What tools or systems do you use for sharing apps and what tools do you use daily?” 32:33 “How much oversight do you have on your analysis and do you ever get stuck in skeptic paralysis?” 35:18 “Do you have any podcast recommendations?” 38:01 “How can organizations resolve the tension between allowing employees space to learn and being productive?” 41:12 “What advice would you give to somebody starting a brand new community within their company?” 46:05 “Any resources for learning modular Shiny apps or tool building in general?” 47:40 “What is the career progression like for a data scientist and is it possible to grow as an individual contributor?”
New data science tools & old laptops on fire | Jenny Bryan | Data Science Hangout
ADD THE DATA SCIENCE HANGOUT TO YOUR CALENDAR HERE: https://pos.it/dsh - All are welcome! We’d love to see you!
We were joined by Jenny Bryan, Senior Software Engineer at Posit, to chat about (setting laptops on fire,) adapting careers to embrace change and new technologies, behind-the-scenes technical advancements powering the R ecosystem with tools like Positron, demystifying project-based workflows, plus LLM integration and best practices in programming.
Listen to this episode to hear us chat about topics like this:
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the benefits and limitations of using Large Language Models (LLMs) in programming. Jenny shared her initial skepticism towards LLMs for coding in R, but her attitude changed significantly when applying LLMs to problems involving languages she was less familiar with, like Rust or TypeScript.
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adapting in your career to embrace change and new technologies. Jenny, who describes herself as being on a “third career”, transitioned from management consulting to a statistics professor, and then to a senior software engineer at Posit. She talks a bit about her career journey and how she’s embracing new stuff (ahem, Typescript) so that she gets to keep doing cool stuff!
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Positron IDE for R package development. She specifically praises Positron’s unique test explorer and reliable console, and its integrated Data Explorer. For many, Positron offers out-of-the-box data science functionality, unlike other IDEs that require extensive customization.
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what new technologies like Ark, Air, and Positron mean for the longterm health of R. Jenny’s been working on lots of nerdy things behind the scenes at Posit and she talks all about how they’re great for developers, package builders, data scientists, and engineers alike.
Another tidbit from this hangout: Jenny gave some advice for those looking to branch into software engineering without formal training: try reading code from admired developers, inviting code reviews, and undertaking small, recreational package development projects to gain practical experience and confidence. She also advocates for adopting a project-oriented workflow (associated with her famous “laptop on fire” remark, of course) using tools like the here package for managing project paths.
Resources mentioned in the video and zoom chat: Positron IDE → https://positron.posit.co/ Happy Git with R → https://happygitwithr.com/ Jenny Bryan’s “Project-oriented workflow” blog post → https://www.tidyverse.org/blog/2017/12/workflow-vs-script/ Air R code formatter → https://posit-dev.github.io/air/ The here() package → https://here.r-lib.org/ Posit Conf → https://posit.co/conference/ Tidy Dev Day 2025 → https://www.tidyverse.org/blog/2025/07/tdd-2025/ R Packages book → https://r-pkgs.org/
If you didn’t join live, you missed a ROARINGLY active chat. Let’s just say, if you’ve ever broken down in tears over a programming project, you’re not alone! Come join us live each week if you’d like to hang out in the chat with us!
► Subscribe to Our Channel Here: https://bit.ly/2TzgcOu
Follow Us Here: Website: https://www.posit.co Hangout: https://pos.it/dsh LinkedIn: https://www.linkedin.com/company/posit-software Bluesky: https://bsky.app/profile/posit.co
Thanks for hanging out with us!
Timestamps 00:00 Introduction 03:39 “Is that a Wooble on your desk?” (Spoiler, it’s a gnome!!) 06:23 “As a builder of data science tools, what are the tool features data scientists want most?” 08:43 “Have you experienced needing to adapt to change recently and how have you embraced it?” 13:46 “What is ‘setting laptops on fire’ about?” 13:50 “How did you decide to change your career a few times?” 21:23 “What are your thoughts on the ease of putting models into production in Python versus R and does it make sense to shift everybody to one language or the other?” 27:30 “How do you navigate the ‘I have a hammer so everything looks like a nail’ feeling when working with emerging tools like LLMs?” 33:24 “Do you have any general advice for those data scientists who find themselves wanting to branch out more into software engineering but don’t have formal training?” 39:39 “Why should I use Positron instead of Versus Code?” 47:57 “Can you speak to the value of developing an R package and how to clear the mental hurdle of it being a huge challenge?” 52:34 “What does your career trajectory look like and what is your advice for other people who are looking to grow their career but don’t know if they want to be an IC or a manager? Does being a manager mean you don’t get to write code anymore?”
Introducing Positron, a new data science IDE - posit conf 2024
Positron is a next-generation data science IDE that is newly available to the community for early beta testing. This new IDE is an extensible tool built to facilitate exploratory data analysis, reproducible authoring, and publishing data artifacts. Positron currently supports these data workflows in either or both Python and R and is designed with a forward-looking architecture that can support other data science languages in the future. In this session, learn from the team-building Positron about how and why it is designed the way it is, what will feel familiar or new coming from other IDEs, and whether it might be a good fit for your own work.
Talk by Julia Silge, Isabel Zimmerman, Tom Mock, Jonathan McPherson, Lionel Henry, Davis Vaughan, and Jenny Bryan
Slide deck 1: https://speakerdeck.com/juliasilge/introducing-positron Slide deck 6: https://speakerdeck.com/jennybc/positron-for-r-and-rstudio-users
Documenting Things: Openly for Future Us - posit::conf(2023)
Presented by Julia Stewart Lowndes
This talk shares practical tips and tangible stories for how intentional approaches to documenting things is helping big distributed teams tackle hard challenges and change organizational culture via NASA Openscapes, NOAA Fisheries Openscapes, & beyond.
I’ll share about documenting things, and how intentional approaches to documentation and onboarding are helping big distributed teams tackle hard challenges and change organizational culture. The goal is to provide concrete tips to help you document things effectively & hear stories of how putting a focus on documentation can be help teams be efficient, productive, and less lonely. I’ll give a short lightning talk (inspired by Jenny Bryan’s Naming Files talk) followed by stories from NASA Openscapes, NOAA Fisheries Openscapes & beyond.
Materials:
- Slides: https://openscapes.github.io/documenting-things
- Blog post: https://openscapes.org/blog/2023-09-27-documenting-things-posit-conf
- Website: https://openscapes.org - links to NASA Openscapes and NOAA Fisheries Openscapes and beyond
- Jenny Bryan’s Naming Files talk - https://github.com/jennybc/how-to-name-files#how-to-name-files
Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.#
Talk Track: Getting %$!@ done: productive workflows for data science. Session Code: TALK-1092
It’s a Great Time to be an R Package Developer! - posit::conf(2023)
Presented by Jenny Bryan and Hadley Wickham
(Due to unforeseen circumstances, Hadley Wickham presented this talk “slide karaoke” style, from materials prepared by Jenny Bryan.)
In R, the fundamental unit of shareable code is the package. As of March 2023, there were over 19,000 packages available on CRAN. Hadley Wickham and I recently updated the R Packages book for a second edition, which brought home just how much the package development landscape has changed in recent years (for the better!).
In this talk, I highlight recent-ish developments that I think have a great payoff for package maintainers. I’ll talk about the impact of new services like GitHub Actions, new tools like pkgdown, and emerging shared practices, such as principles that are helpful when testing a package.
Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.#
Talk Track: Package development. Session Code: TALK-1132
How to name files - Jennifer Bryan
Low-tech common sense about filenames. The holy trinity is: +machine readable +human readable +sorted in a useful way
More at https://github.com/jennybc/how-to-name-files
Posit Meetup | Jake Riley, Children’s Hospital of Philadelphia | Translating Facts to Insights
RStudio Healthcare Meetup:
Translating facts into insights at Children’s Hospital of Philadelphia Led by Jake Riley, data analyst at The Children’s Hospital of Philadelphia
Abstract: {headliner} is a new R package to add dynamic, insightful text to plots and reports. {headliner} generates useful talking points that users can string together using {glue} syntax. This makes it easy to write an informative sentences without adding a lot of technical debt to a project. Learn how to get started with {headliner} and ways we have used it at The Children’s Hospital of Philadelphia.
Speaker Bio: Jake Riley is a data analyst at The Children’s Hospital of Philadelphia. He is the author of several R packages related to data visualization and automated exploratory analysis. You can find his published work [simplecolors] and [shinyobjects] on CRAN with more packages on the way.
Timestamps: 0:49 - Start of talk 1:25 - Dashboards focused on facts vs. insights 2:56 - What’s a good title for a chart? 5:09 - Intro to headliner package 7:41- using glue() under the hood 14:04 - helpers for working with data frames: compare_conditions() 18:41 - using ggtext 21:27 - example using pixar_films 23:40 - how they’ve used it at CHOP 28:05 - Next steps for headliner package 29:32 - Start of Q&A session
Questions: 29:32 - Can you use any package you want in your organization? 31:13 - How do you load previous datasets to compare to current datasets? 32:48 - When you mentioned a front page on RStudio Connect (with the headlines), what is that? 33:25 - Is anyone using this for manuscripts at CHOP now? 36:24 - What has the adoption of R or Python been within the hospital analytics team? 37:28 - My manager is very leery of R because of technical depth. Any suggestions for convincing her of R’s value? 42:22 - How does CHOP use R for non-clinical analysis? 43:36 - How do you train new people to use R? 46:28 - How do you compare last week’s analysis to this week’s? 49:37 - Were there any major challenges in creating the hospital’s internal package?
Resources/links shared: Jake’s LinkedIn: https://www.linkedin.com/in/jake-riley-70736a3/ headliner package: https://github.com/rjake/headliner waldo package: https://www.tidyverse.org/blog/2020/10/waldo/ Examples of R in Life Science & Healthcare: https://www.rstudio.com/champion/life-science Chris Bumgardner’s talk on building an R-based analytic practice at Children’s Wisconsin: https://youtu.be/pHZ8dsc0PhY simplecolors package to generate hex codes using uniformly named colors: https://rjake.github.io/simplecolors/ R Packages book by Hadley Wickham & Jenny Bryan: https://r-pkgs.org/
Meetup Links: Future events: rstd.io/community-events-calendar If anyone’s interested in speaking at a future meetup, we’d love to hear from you too! rstd.io/meetup-speaker-form
Jenny Bryan | Help me help you: creating reproducible examples | RStudio (2018)
What is a reprex? It’s a reproducible example. Making a great reprex is both an art and a science and this webinar will cover both aspects. A reprex makes a conversation about code more efficient and pleasant for all. This comes up whenever you ask someone for help, report a bug in software, or propose a new feature. The reprex package (https://reprex.Tidyverse.org ) makes it especially easy to prepare R code as a reprex, in order to share on sites such as https://community.rstudio.com , https://github.com , or https://stackoverflow.com . The habit of making little, rigorous, self-contained examples also has the great side effect of making you think more clearly about your programming problems.
Webinar materials: https://rstudio.com/resources/webinars/help-me-help-you-creating-reproducible-examples/
About Jenny: Jenny is a software engineer on the tidyverse team. She is a recovering biostatistician who takes special delight in eliminating the small agonies of data analysis. Jenny is known for smoothing the interfaces between R and spreadsheets, web APIs, and Git/GitHub. She’s been working in R/S for over 20 years and is a member of the R Foundation. She also serves in the leadership of rOpenSci and Forwards and is an adjunct professor at the University of British Columbia
Jenny Bryan | Lazy evaluation | RStudio (2019)
The “tidy eval” framework is implemented in the rlang package and is rolling out in packages across the tidyverse and beyond. There is a lively conversation these days, as people come to terms with tidy eval and share their struggles and successes with the community. Why is this such a big deal? For starters, never before have so many people engaged with R’s lazy evaluation model and been encouraged and/or required to manipulate it. I’ll cover some background fundamentals that provide the rationale for tidy eval and that equip you to get the most from other talks.
VIEW MATERIALS https://github.com/jennybc/tidy-eval-context#readme
About the Author Jenny Bryan Jenny is a recovering biostatistician who takes special delight in eliminating the small agonies of data analysis. She’s part of Hadley’s team, working on R packages and integrating them into fluid workflows. She’s been working in R/S for over 20 years, serves in the leadership of rOpenSci and Forwards, and is an Ordinary Member of the R Foundation. Jenny is an Associate Professor of Statistics (on leave) at the University of British Columbia, where she created the course STAT 545
Irene Steves | Teaching data science with puzzles | RStudio (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.
VIEW MATERIALS https://github.com/isteves/ds-puzzles
About the Author Irene Steves This summer I was an intern at RStudio, where I worked with Jenny Bryan to develop a series of coding challenges to cultivate and reward the mastery of R and the tidyverse. I was previously a Data Science Fellow at the National Center for Ecological Analysis and Synthesis (NCEAS), where I reviewed data submissions to a national repository for completion, clarity, and data management best practices. As a fellow, I also collaborated on a number of open science projects to improve access to Ecological Metadata Language (EML) and datasets in the DataONE network (see metajam, dataspice)
