Positron

Isabella’s Bluesky: https://bsky.app/profile/ivelasq3.bsky.social Libby’s Bluesky: https://bsky.app/profile/libbyheeren.bsky.social Isabella’s LinkedIn: https://www.linkedin.com/in/ivelasq/ Libby’s LinkedIn: https://www.linkedin.com/in/libbyheeren/

Resources mentioned in the video: Positron → https://positron.posit.co/ VS Code Source Control → https://code.visualstudio.com/docs/sourcecontrol/overview Positron “create issues” triggers (add your own, too!) → positron://settings/githubIssues.createIssueTriggers GitHub → https://github.com/ Linking a GitHub issue to a pull request → https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue GitHub commands for PRs → https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue Git → https://git-scm.com/ Quarto → https://quarto.org/ GitHub Pull Requests and Issues Extension → https://marketplace.visualstudio.com/items?itemName=GitHub.vscode-pull-request-github Azure DevOps → https://azure.microsoft.com/en-us/products/devops/ Happy Git with R → https://happygitwithr.com/ Software Carpentry Git → https://swcarpentry.github.io/git-novice/

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Thanks for hanging out with us!

Timestamps of Questions / Topics 00:00 Introduction 02:56 Creating a Quarto book project in Positron 05:54 Initializing a Git repository and publishing to GitHub 06:49 Creating a .gitignore file 08:00 “Do you have to create a GitHub account before starting this kind of project?” 11:53 Staging changes and making the initial commit 13:34 Adding a collaborator on GitHub 14:25 Setting up branch protection rules 15:25 “Was that push to GitHub the initialization of the GitHub repo?” “What if you already had a GitHub repo with that same name, would you get a warning in positron?” 18:50 Working with pull requests and issues directly in Positron 20:18 Cloning an existing repository 24:09 Undoing your last commit 24:41 Stashing staged changes 25:12 Creating a new branch 26:03 Applying changes by popping a stash 27:03 Creating a pull request 28:37 How to put your activity bar in Positron to the top 29:40 Reviewing and merging a pull request 32:46 Deleting local and remote branches 36:08 “Are there benefits to doing things within positron vs the GitHub UI?” 39:13 “Do you know how to delete a branch if it’s an older rogue branch?” 41:40 Using keywords to automatically create GitHub issues 43:24 “Is the functionality similar if you’re working with an internal organization like Azure DevOps version of Git?” 44:12 “What is the best way to get an orientation into the world of Git and GitHub?” 46:42 Pulling and synchronizing branches 49:01 How to resolve merge conflicts

Isabel Zimmerman, Isabella Velásquez

ADD THE DATA SCIENCE HANGOUT TO YOUR CALENDAR HERE: https://pos.it/dsh - All are welcome! We’d love to see you!

This week’s guests were Tom Grace, Tech Lead on the Platform Team, and Darren Cope, Posit Subject Matter Expert, both at HMRC! We sadly lost connection with Darren due to wifi issues, but we hope to chat with him for a special video soon. We missed you Darren!

Some topics covered in this week’s Hangout were managing Posit platforms and tools for nearly 600 analysts, strategies for evaluating and introducing new tools and packages in a large organization, utilizing dynamic compute allocation to let analysts manage their own processing budgets, and navigating change management by building empathy (empathy is always the answer, we love to see it!).

Resources mentioned in the video and chat: Johnson & Johnson Positron Webinar → https://pos.it/j-and-j Announcing the Positron Notebook Editor for Jupyter Notebooks → https://posit.co/blog/announcing-the-positron-notebook-editor-for-jupyter-notebooks/ Accessibility in Data Visualization Course → https://openvisualizationacademy.org/courses/accessibility-in-data-visualization/ Posit Package Manager → https://posit.co/products/enterprise/package-manager/

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Thanks for hanging out with us!

Timestamps 00:00 Introduction 06:10 “Do you still have a lot of SAS users inside of your org?” 07:37 “Could you tell us about an example of a type of problem you tackle, the type of data that you see, and the tools you use?” 10:04 “What does that sort of composition look like for you as far as the people that you’re serving?” 11:15 “So when you say Python, is that like Streamlit apps being launched in Connect?” 11:46 “When people suggest new tools that they want to use, what is the most helpful information that they share? Can you help teach us how to get things approved by our own teams?” 18:59 “How do I find time for data science training if I’m struggling to complete routine work tasks?” 26:52 “Do stakeholders still want the reports to be in Excel?” 29:38 “Could you give us an example of what large processing means for your team on the regular?” 31:50 “Do you have any advice for handling this and providing reassurance?” 35:12 “How often do you get to upgrade your Posit environment to bring in new packages, features, etcetera?” 35:29 “When someone wants to use a package or a new tool, do you have a process that they have to go through to get packages approved and then also versions of R and Python?” 38:16 “How do you communicate technical changes with people across the organization.” 42:07 “Can you remind us the scale that we’re talking about here as far as the number of end users who might be in one of those channels asking for help?” 42:53 “What was the change management process like from your experience, and how did you overcome organizational inertia when moving to Posit?” 47:14 “As a leader, how do you raise everyone’s level so the whole team performs like your top players?”

Sara’s Bluesky: https://bsky.app/profile/sara-altman.bsky.social Sara’s LinkedIn: https://www.linkedin.com/in/sarakaltman/ Sara’s GitHub: https://github.com/skaltman Posit AI Newsletter by Sara and Simon: https://posit.co/blog/?category=roundups

Resources from the hosts and chat:

Positron IDE → https://positron.posit.co/ Databot Extension → https://positron.posit.co/databot.html Getting started with Positron Assistant → https://positron.posit.co/assistant-getting-started.html Posit Assistant (Private Beta) → https://posit-ai-beta.share.connect.posit.cloud/ Reviewer Package (by Simon Couch) → https://github.com/simonpcouch/reviewer ellmer Package → https://elmer.tidyverse.org/ chatlas Package → https://github.com/posit-dev/chatlas Read the Posit AI Newsletter → https://posit.co/blog/?category=roundups Sign up to get the Posit AI Newsletter → http://pos.it/ai-news Simon’s blog post about local LLMs not quite being ready for primetime → https://posit.co/blog/local-models-are-not-there-yet/ Join the waitlist for Posit AI in RStudio → https://posit.co/products/ai/ Posit AI Known Issues & FAQs → https://posit-ai-beta.share.connect.posit.cloud/#frequently-asked-questions-faqs Blog post from Simon and Sara about Privacy and LLMs → https://posit.co/blog/trust-llm-tools/ DS Lab YouTube playlist → https://youtube.com/playlist?list=PL9HYL-VRX0oSeWeMEGQt0id7adYQXebhT&si=7tmU6EAJpO5S7GBh

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Thanks for learning with us!

Timestamps 00:00 Introduction 07:23 “Would you mind real quick just briefly explaining the differences between Positron Assistant and Databot?” 15:01 “Is there any way to configure reasoning efforts when signing in with GitHub Copilot?” 15:49 “Does DataBot already support other providers beyond Cloud?” 20:36 “What is the cases with monetary penalty in the console output?” 22:14 “Do you happen to know if the column names of the dataset are very, very messy?” 23:18 “Can you add skills to DataBot?” 26:36 “This code isn’t being saved anywhere. So where does it go?” 27:38 “There a way to know what all the slash commands are?” 28:51 Requesting Databot to use the namespace operator 33:58 “Is there a way to search within that Databot pane?” 39:34 “Have you noticed any time differences with how quickly things run-in RStudio versus Positron?” 40:33 “What happens if you open that URL that it mentions at the bottom in your browser?” 40:50 Clarifying the difference between Posit Assistant and Positron Assistant 43:18 “What is the typical token burn rate?” 53:31 “Is this on CRAN and working in both Positron and RStudio?”

Simon Couch

On this call, Libby Heeren is joined by Edgar Ruiz as they walk through how mall works (with ellmer) in R, and then python. The mall package lets you use LLMs to process tabular or vectors of data, letting you do things such as feeding it a column of reviews and asking mall to use an anthropic model via ellmer to add a column of summaries or sentiments. Follow along with the code here: https://github.com/LibbyHeeren/mall-package-r

Hosting crew from Posit: Libby Heeren, Isabella Velasquez, Edgar Ruiz

Edgar’s Bluesky: https://bsky.app/profile/theotheredgar.bsky.social Edgar’s LinkedIn: https://www.linkedin.com/in/edgararuiz/ Edgar’s GitHub: https://github.com/edgararuiz

Resources from the hosts and chat:

Ollama → https://ollama.com/download Posit Data Science Lab → https://posit.co/dslab mall package → https://mlverse.github.io/mall/ ellmer package → https://elmer.tidyverse.org/ Libby’s Positron theme (Catppuccin) → https://marketplace.visualstudio.com/items?itemName=Catppuccin.catppuccin-vsc GitHub repo with Libby and Edgar’s code → https://github.com/LibbyHeeren/mall-package-r LLM providers supported by ellmer → https://ellmer.tidyverse.org/index.html#providers vitals package → https://vitals.tidyverse.org/ chatlas package → https://posit-dev.github.io/chatlas/ polars package → https://pola.rs/ narwhals package → https://narwhals-dev.github.io/narwhals/ pandas package → https://pandas.pydata.org/ LM Studio → https://lmstudio.ai/ Simon Couch’s blog → https://www.simonpcouch.com/ Edgar’s dataset: TidyTuesday Animal Crossing Dataset (May 5, 2020) → https://github.com/rfordatascience/tidytuesday Libby’s dataset: Kaggle Tweets Dataset → https://www.kaggle.com/datasets/mmmarchetti/tweets-dataset Blog from Sara and Simon on evaluating LLMs → https://posit.co/blog/r-llm-evaluation-03/ Data Science Lab YouTube playlist → https://www.youtube.com/watch?v=LDHGENv1NP4&list=PL9HYL-VRX0oSeWeMEGQt0id7adYQXebhT&index=2 AWS Bedrock → https://aws.amazon.com/bedrock/ Anthropic → https://www.anthropic.com/ Google Gemini → https://gemini.google.com/ What is rubber duck debugging anyway?? → https://en.wikipedia.org/wiki/Rubber_duck_debugging

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Thanks for learning with us!

Timestamps 00:00 Introduction to Libby, Isabella, Edgar, and the mall package + ellmer package 07:14 “What’s the difference between using mall for these NLP tasks versus traditional or classical NLP?” 09:37 “Can mall be used with a local LLM?” 17:32 “What kind of laptop specs should I realistically have to make good use of these models?” 22:12 “Are you limited to three output options?” 22:55 “Can mall return the prediction probabilities?” 24:14 “What are a rule of thumb set of specs for a machine so local LLMs are practically feasible?” 24:47 “Would that be in the additional prompt area where you’re defining things?” 25:04 “You could use the vitals package to compare models, right?” 25:24 “Can we use LM Studio instead of Ollama?” 28:35 “How do you iterate and validate the model?” 36:39 “Why use paste if it is all text?” 37:31 “Are these recent tweets (from X) or older ones from actual Twitter?” 40:23 “Is there a playlist for the Data Science Labs on YouTube?” 46:11 “Does that mean that the python version does not work with pandas?” 50:14 “Where is this data set from?”

Edgar Ruiz, Simon Couch

ADD THE DATA SCIENCE HANGOUT TO YOUR CALENDAR HERE: https://pos.it/dsh - All are welcome! We’d love to see you!

This week’s guest was Brijesh Chejerla, Lead Data Scientist at Blue Cross Blue Shield of Florida (Florida Blue)!

Some topics covered in this week’s Hangout were how to transition into different industries (such as transitioning from academia into motorsports ️), the importance of thinking like an architect and learning system design, and the impact of AI coding agents on the future of data science roles.

Resources mentioned in the video and chat: Posit::conf(2026) Call for Talks → https://posit.co/blog/posit-conf-2026-call-for-talks/ Call for Talks Q&A Video → https://youtu.be/aKN8qlLjld4 Johnson & Johnson Positron Webinar → https://pos.it/j-and-j R!sk Conference 2026 → https://rconsortium.github.io/Risk_website/ Rainbow R Conference 2026 → conference.rainbowr.org Think Like a CEO Book → https://www.amazon.com/Think-Like-CEO-reacting-control/dp/B09LGWT11C Sports Analytics and Data Science Book → https://www.amazon.com/Sports-Analytics-Data-Science-Winning/dp/0133886433 Portfolio Presentation Walkthrough → https://jedmund.com/universe/portfolio-recording Register for Data Science Lab → https://pos.it/dslab

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Thanks for hanging out with us!

Timestamps: 00:00 Introduction 03:01 “What team you support at BCBS of Florida?” 03:37 “Could you talk a little bit about your stint in motorsports analytics?” 05:23 “Favorite example of data science applied in football or sports in general?” 09:41 “Would you be able to provide some resources for people who are interested in machine learning and football?” 13:04 “How did you pick an industry?” 18:57 “What is the most commonly used ML technique and where does deep learning come into play in your day to day job?” 22:45 “What tools do your teams use?” 27:31 “How did you so successfully transfer that IT admin ownership over to someone else?” 30:53 “How do you think AI is going to impact data science roles?” 38:48 “How do you quickly become the data expert?” 43:49 “I’ve been told that I need to have a portfolio to get hired. How true is that?” 46:42 “What career advice has helped you in your career?”

On this call, Libby Heeren is joined by Andrew Heiss as he demonstrates some tips and tricks about his personal workflow and tools that he actually uses to make life easier in Positron. This is the ultimate list of data life hacks to make your workflow soooo much nicer. Check out Andrew’s blog post here to follow along with the tools he mentions: https://andhs.co/dsl

Hosting crew from Posit: Libby Heeren, Isabella Velasquez

Andrew’s Website: https://www.andrewheiss.com/ Andrew’s Bluesky: https://bsky.app/profile/andrew.heiss.phd Andrew’s LinkedIn: https://www.linkedin.com/in/andrewheiss/

Resources from the hosts and chat:

Andrew’s blog post containing links to all of the tools he mentions: https://www.andrewheiss.com/blog/2026/01/13/dsl-positron-workflow/ Open VSX Registry: https://open-vsx.org/ DataPasta: https://milesmcbain.github.io/datapasta/ Pastum (like datapasta for Positron): https://open-vsx.org/extension/atsyplenkov/pastum Positron Project docs: https://positron.posit.co/migrate-rstudio-rproj.html Garrick’s data science extension bundle package: https://github.com/gadenbuie/positron-plus-1-e Emil’s keyboard shortcut blog post: https://emilhvitfeldt.com/post/positron-key-bindings/ Native Tabs for Mac: https://lucasprag.com/posts/underrated-vscode-feature-native-tabs/ Andrew’s posit::conf(2025) Talk: https://youtu.be/UCloM4GcfVY Arc browser that Andrew is using: https://arc.net/ Andrew’s YAML headers he sets up using espanso: https://github.com/andrewheiss/espanso/blob/52da6c43c6d1ebaf3231770b1b66971d1dfb374a/match/markdown-pandoc-quarto.yml#L118

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Thanks for learning with us!

Timestamps: 00:00 Introduction 01:50 Switching to Positron full-time 03:19 Extensions in Positron 04:44 How to evaluate if an extension is safe 07:05 Air extension (auto-formatting) 08:21 Better Comments extension 10:15 Moving the Activity Bar 12:20 Pastum extension (DataPasta equivalent) 14:26 Rainbow CSV extension 15:34 Spell Right extension 17:34 Managing projects in Positron vs RStudio 20:18 “Do you know if there are extensions… that will conditionally format cells?” 20:40 “Do you explicitly add a dot here file?” 21:44 Project Manager extension 25:34 “How did you discover all of these?” 26:38 “How is GitHub integrated into Positron?” 29:10 Peacock extension 31:16 The Connections pane 36:38 “When I change the Peacock color, it’s changing colors for everything.” 37:59 “Does he use any DuckDB extensions?” 39:05 Raycast 43:35 Raycast scripts 44:30 NotebookLM 45:31 “Is there a hack to manage a repo that is both a project and an R package?” 48:00 Espanso 53:15 “Is Raycast a replacement for Spotlight and Bartender?” 54:00 “Is there an easy way to see all of the shortcuts?”

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 Adrian Perez, Head of People Analytics at GitLab, to chat about the role of people analytics in business, how he’s navigated the changing HR-data-sphere, advice for moving from an individual contributor to a manager, and the modern data stack used at GitLab.

In this Hangout, we explore one of our favorite topics here: People Analytics! Adrian discusses the scale at which companies should establish a dedicated function and shares a specific case study from his time at H-E-B where survival analysis was used to improve recruiting processes. He also provides insights on how to manage relationships with stakeholders who may be skeptical of data results, emphasizing the importance of partnership over purely proving someone wrong. (Libby heavily agrees - it’s about human relationships and trust!)

Resources mentioned in the video and zoom chat: GitLab Company Handbook (AMAZINGLY open resource) → https://handbook.gitlab.com/ GitLab People Analytics Team Page → https://handbook.gitlab.com/handbook/people-group/people-ops-tech-analytics/people-analytics/ Positron IDE → https://positron.posit.co/

If you didn’t join live, one great discussion you missed from the zoom chat was about advice for first-time managers, including a recommendation for the book “The Making of a Manager” by Julie Zhuo. Let us know below if you’d like to hear more about the IC-to-manager move!

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Thanks for hanging out with us!

Timestamps: 00:00 Introduction 03:58 “Do you have a enormous team? Are you guys small and mighty?” 06:26 “Is there a minimum company size before people analytics becomes worthwhile?” 09:25 “Can you share some specific types of analysis or modeling tasks that are done in people analytics?” 15:30 “How do you manage HR professionals when they don’t like the results that the data showed them?” 19:28 “Does that include implementing third party applicant tracking systems, keyword analysis?” 24:26 “Any advice you’re willing to share for a first time manager?” 30:35 “What tools do you use at GitLab?” 33:59 “Have you tried Positron?” 35:00 “How do you think that this would work in the sports industry?” 39:24 “How do you manage to respect privacy of the data you work with?” 44:18 “Have you done any work on skills analysis and or leveraging graph databases?” 46:42 “Is there a qualitative element to your analysis as well?” 48:19 “Is people analytics considered a subset of human factors?” 50:35 “Is it possible to break into people analytics with data experience but no HR experience?” 51:12 “Could you leave us with a piece of career advice?”

Helpful Links: Download Positron: https://positron.posit.co/ Databricks Asset Bundles: http://docs.databricks.com/dev-tools/bundles GitHub Repo for Demo: https://github.com/blairj09/databricks-data-engineering Lakeflow Declarative Pipelines: http://docs.databricks.com/aws/en/ldp Talk to us about integrating Posit & Databricks: https://posit.co/schedule-a-call/

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 Isabel Zimmerman and Davis Vaughan, Software Engineers at Posit, to chat about the life of an open source developer, strategies for navigating complex codebases, and how to leverage AI in data science workflows. Plus, NERDY BOOKS!

In this Hangout, we explore the differences between maintaining established ecosystems like the Tidyverse as well as building new tools like the Positron IDE. Davis and Isabel (and sometimes Libby ) share practical advice for developers, such as the utility of AI for writing tests and “rubber ducking”, and their various approaches to writing accessible documentation that bridges the expert-novice gap.

Resources mentioned in the video and zoom chat: Positron IDE → https://posit.co/positron/ Air (R formatter) → https://posit-dev.github.io/air/ Python Packages Book (free) → https://py-pkgs.org/ R Packages Book (free) → https://r-pkgs.org/ DeepWiki (AI tool mentioned for docs) → https://deepwiki.com/tidyverse/vroom

If you didn’t join live, one great discussion you missed from the zoom chat was about Brandon Sanderson’s Cosmere books and the debate between starting with Mistborn vs. The Stormlight Archive. Are you a Cosmere fan?! Which book did you start with? (Libby started with Elantris years before picking up Mistborn Era 1 book 1, but she’d now recommend maybe starting with Warbreaker!)

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Thanks for hanging out with us!

Timestamps: 00:00 Introduction 04:41 “What does a day in the life of an open source dev look like?” 09:43 “What got you into building your own R packages?” 13:00 “Personal tips for working with code bases you’re not familiar with?” 16:35 “How much of what you build is in R/Python vs. lower-level languages?” 19:57 “Does Air work inside code chunks in Positron?” 20:12 “Changing the Python Quarto formatter in Positron without an extension” 22:56 “What do your side projects look like?” 26:40 “How do you approach writing documentation?” 30:55 “What interesting trends in data science are you noticing?” 33:38 “How do you leverage AI in your work?” 37:30 “What are the hexes on Davis’s back wall?” 38:50 “What career advice would you give to someone in a similar position?” 43:45 “How can I be more resilient when things go wrong?” 47:59 “Do you have keyboard preferences?” 49:25 “What is the best way to report bugs in packages?” 50:56 “Open source dev work vs. in-house dev work” 51:50 “Tips for getting started with Positron”

Davis Vaughan, Isabel Zimmerman

Alex Chisholm’s LinkedIn: http://www.linkedin.com/in/chisholm1

Resources from the hosts and chat:

Posit Connect Cloud for deploying Shiny apps in the modern era: https://connect.posit.cloud/ Install Positron: https://positron.posit.co/ Simon Couch’s blog post on local LLMs not being good enough yet: https://www.simonpcouch.com/blog/2025-12-04-local-agents/ Blue-Green Shiny App Deployments using Posit Connect posit::conf(2025) talk by Ryszard Szymański: https://youtu.be/QEEGLWj0nas Digital Ocean: https://www.digitalocean.com/ Ollama local LLM: https://ollama.com/ py-sidebot app template: https://shiny.posit.co/py/templates/sidebot/ querychat app template: https://shiny.posit.co/py/templates/querychat/ Dan Chen mentioned Render in the chat as an alternative to Digital Ocean: https://render.com/ Alex Chisholm’s AB testing GitHub repo example: https://github.com/alex-chisholm/shiny-r-abtesting Edward in the chat shared a GitHub repo for using GitHub actions to execute remote SSH commands: https://github.com/appleboy/ssh-action Abu in the chat shared blue-green vs. canary deployments: https://octopus.com/devops/software-deployments/blue-green-vs-canary-deployments/ Frank in the chat mentioned Simon’s blog on using local LLMs with the chores package: https://www.simonpcouch.com/blog/2025-12-10-chores-0-3-0/

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Thanks for learning with us!

Timestamps 00:00 Introduction 03:03 Meaningful applications and value creation 05:31 The evolution of Shinyapps.io and Posit Connect 08:12 DigitalOcean and Droplets 09:36 DigitalOcean vs. commercial cloud providers, 11:48 Comparisons: DigitalOcean, Azure, and AWS 14:47 Replicating local environments with Docker 16:51 The open-source Shiny Server 18:20 Use case: University of Illinois CITL 20:02 Key considerations for deployment decisions 21:53 GitHub Actions and version control 23:31 Addressing single points of failure and maintainability 24:38 Posit Connect Cloud features and portfolio 26:01 Beyond Shiny: Quarto, Streamlit, and Dash 27:07 Handling secrets and database credentials 28:56 Custom vanity links vs. UUIDs 30:04 Blue-Green deployment strategies 31:55 “Is it easy to set up a developer workflow?” 34:46 Guardrails for AI powered apps and token usage 37:32 Small language models and Ollama 38:29 Sidebot AI demo and LLM integration 39:41 Understanding manifest.json and dependencies 45:00 Automatic publish on GitHub push 46:51 The future of Shinyapps.io and migration 48:33 “Did you just build a custom agent for that specific dashboard?” 51:43 Publishing from RStudio IDE to Connect Cloud 54:16 Preview: Inspecting website APIs for data harvesting

Simon Couch

Emil’s socials and urls: website: https://emilhvitfeldt.com/ GitHub: https://github.com/emilhvitfeldt Bluesky: https://bsky.app/profile/emilhvitfeldt.bsky.social LinkedIn: https://www.linkedin.com/in/emilhvitfeldt/

Resources from the hosts and chat:

Advent of Code: https://adventofcode.com/ Install Positron: https://positron.posit.co/ Eric Wastl, Advent of Code: Behind the Scenes: https://www.youtube.com/watch?v=_oNOTknRTSU AoC Subreddit: https://www.reddit.com/r/adventofcode/ Kieran Healy shared a reddit post with an Advent of Code answer done in Minecraft: https://www.reddit.com/r/adventofcode/comments/1pbeyxx/2025_day_01_part_2_advent_of_code_in_minecraft/ Emil’s Solutions: https://github.com/EmilHvitfeldt/rstats-adventofcode Emil’s helper package: https://github.com/EmilHvitfeldt/aocfuns purrr::accumulate() function: https://purrr.tidyverse.org/reference/accumulate.html

And, for anyone hangin’ in there at the end, Emil updated us on Discord that he figured out why his cumsum() didn’t work: he forgot to start the dial at 50! Once you fix that, it works to solve part 1 :)

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Thanks for learning with us!

Timestamps 00:00 Introduction 01:01 Tour of the Advent of Code website 02:30 Dashboard overview and puzzle schedule 03:23 How to view and access previous years’ events 03:37 Structure of puzzles: Two parts and stars 04:40 Understanding the global leaderboard 05:08 “Does that ASCII art build itself? 06:16 Setting up private leaderboards for friend 07:54 Starting Day 1: Story prompt and mechanics 09:30 Understanding unique puzzle inputs 10:51 Submission feedback and delay penalties 11:44 Safe dial logic: Left, Right, and circularity 12:50 Starting position and Part 1 success criteria 14:09 Setting up the project in Positron 16:26 Strategy for speed: Reading from the bottom up 18:49 Problem-solving strategies: Pen, paper, and visualization 19:22 Walking through the logic with a sample case 20:52 Coding Part 1: Data parsing and vectorization 23:17 Positron keyboard shortcuts for duplicating lines 24:40 Debugging the logic and handling negative numbers 26:03 Explaining the Modulo operator (%%) 28:15 Managing large inputs of over 4,000 instructions 29:21 Submitting Part 1 and transitioning to Part 2 32:03 Part 2 challenge: Counting zero “clicks” 34:02 Brainstorming Part 2 code modifications 36:19 Checking important warnings for edge cases 37:00 Coding Part 2: Nested loops and incrementing counters 38:23 Hint: Modulo vs. integer division 40:40 Success with the Part 2 test case 42:30 Alternative method: Vectorized cumulative sums 45:29 “What’s the difference between % and %%?” (percent vs modulo) 46:50 Mathematical optimization to avoid inner loops

Emil Hvitfeldt

Resources from the hosts and chat: Install Positron: https://positron.posit.co/ Positron docs on keyboard shortcuts: https://positron.posit.co/keyboard-shortcuts.html Nathan Jeffery’s “click to open a .RDS file” keybinding: https://nathan-jeffery.netlify.app/blog/2025-08-26-read-rds-positron/ Positron R pipe setting (paste in browser and it’ll open in Positron): positron://settings/positron.r.pipe One of Dan Chen’s faves, the native tab feature in VSCode + Positron: https://lucasprag.com/posts/underrated-vscode-feature-native-tabs/ The list of RStudio keybindings that you get when you turn on RStudio keybindings in Positron: https://positron.posit.co/migrate-rstudio-keybindings.html Indent rainbow extension: https://open-vsx.org/extension/oderwat/indent-rainbow Rainbow brackets setting (paste in browser and it’ll open in Positron): positron://settings/editor.bracketPairColorization.enabled Setting hierarchy (User vs Workspace settings) in Positron: https://code.visualstudio.com/docs/configure/settings#_settings-precedence Rainbow CSV extension (not by Posit): https://marketplace.visualstudio.com/items?itemName=mechatroner.rainbow-csv Positron +1ePositron, an extension pack for dev and data science, by Garrick Aden-Buie: https://open-vsx.org/extension/grrrck/positron-plus-1-e Publishing from VS Code or Positron: https://docs.posit.co/connect/user/publishing-positron-vscode/ Posit Connect Cloud plans: https://connect.posit.cloud/plans Enter Folder extension that Libby mentions: https://open-vsx.org/extension/xiangda/enter-folder Catppuccin themes (shared by Rory Lawless, and now some of Libby’s favorites!): https://open-vsx.org/extension/Catppuccin/catppuccin-vsc

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Thanks for learning with us!

Timestamps 00:00 Introduction 00:42 Guest Introductions: Isabel and Davis 02:41 Positron Settings overview 04:11 How to enable “Format on Save” 04:34 “How do I open settings in JSON or UI?” 05:10 Auto Save on focus change 08:26 Enabling RStudio key bindings 09:28 “Why doesn’t the cursor move with code edits?” 12:18 User vs. Workspace settings 14:34 Creating and using Profiles 16:13 “Can I use the magrittr pipe with Control+Shift+M?” 17:23 Searching and managing keyboard shortcuts 19:42 Creating custom code snippets 21:31 The Indent Rainbow extension 24:04 Enabling rainbow parenthesis/brackets 25:08 Managing Python and R interpreters 26:32 Rearranging and hiding UI panes 28:04 Rainbow CSV and favorite extensions 29:26 Using the Enter Folder extension 31:05 Understanding the setting hierarchy 32:48 Adding symbols to Quick Open search 36:00 “Is there a way to shift focus using keyboard shortcuts?” 38:04 Modifying keybindings JSON for specific languages 39:20 “How do you find trustworthy extensions?” 43:11 “How can I publish to shinyapps.io from Positron?” 44:03 Deploying with Posit Publisher and Connect Cloud 48:32 Customizing themes with RainGlow extension 50:36 “Is there an Import Data Set wizard in Positron?” 53:01 Conclusion and community resources

Davis Vaughan, Garrick Aden-Buie, Isabel Zimmerman

• {vitals}: Large Language Model Evaluations https://vitals.tidyverse.org/
• {mcptools}: Model Context Protocol for R https://posit-dev.github.io/mcptools/
• {btw}: A complete toolkit for connecting R and LLMs https://posit-dev.github.io/btw/
• {gander}: High-performance, low-friction Large Language Model chat for data scientists https://simonpcouch.github.io/gander/
• {chores}: A collection of large language model assistants https://simonpcouch.github.io/chores/
• {predictive}: A frontend for predictive modeling with tidymodels https://github.com/simonpcouch/predictive
• {kapa}: RAG-based search via the kapa.ai API https://github.com/simonpcouch/kapa
• Databot https://positron.posit.co/dat

Simon Couch

Learn more about the Posit partnership with Snowflake: https://posit.co/use-cases/snowflake/ Get the Posit Team Native App: https://pos.it/Team-Native-App-Snowflake

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 Kevin Dalton, Senior Data Scientist at Great American Insurance Group, to chat about data science in the insurance industry, MLOps and productionalization strategies, Bayesian modeling, and career development.

In this Hangout, we explore MLOps and productionalization strategies, especially the distinction between “little P” and “big P” production. Kevin explained that “small p” production involves internal dashboards, interactive applications, or analytics reports used to support the research process and assess the business, generally having a lower risk profile. In contrast, “big P” production refers to ML models deployed for inference in core business systems, which demand strict Service Level Agreements (SLAs). Kevin noted that the industry is moving towards automated, cloud-centric, real-time inference engines, although production systems can still be as simple as running a notebook over new data.

Resources mentioned in the video and zoom chat: The (new!) Data Science Lab on Tuesdays → https://pos.it/dslab Bayes Rules! Book → https://www.bayesrulesbook.com/ Positron link → https://positron.posit.co/

If you didn’t join live, one great discussion you missed from the zoom chat was about the humorous observations regarding Kevin’s unique professional history, with some referring to it as the “skydiving to actuary pipeline” There was some speculation about whether professional skydivers have “No fear to deploy models” and then there was a subsequent realization about all the insurance needed for a skydiving business. That tracks!

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Timestamps 00:00 Introduction 05:06 “What does it actually mean to put models into production at an insurance company?” 07:27 “How do you actually explain that to people at the company that there’s this need for two different types of production?” 09:21 “Have you guys, in a large company, found any application for smaller language models in, like, production pipelines?” 10:17 “Are there any lessons from the skydiving experience that you apply to your data science work?” 12:45 “What recent innovative ML models in the insurance sectors have you brought live if you’re allowed to share?” 17:33 “I’m just curious to hear from you or others in chat who spend a lot of time in R if there are strategies you found effective in bridging the gap to using Python.” 20:54 “What was the main thing that got you from “who is this for?” when you first opened Positron to now using it?” 22:46 “Could you share a little bit about what your tool stack looks like at Great American Insurance Group?” 24:27 “So you actually run Posit within Snowflake. Is that right?” 26:32 “What sort of guardrails are you using that are specific to insurance to guard against drift?” 29:26 “Do you think that’ll be the future when it comes to test driven development?” 30:55 “What are some of your favorite public data sources for trying to quantify and model things like geopolitical risk?” 32:07 “If you wanna learn more about using tools you mentioned for building synthetic data, where would you recommend that people start?” 34:27 “So with the AI evolving, what kind of techniques are being recently used?” 35:28 “Broadly, how is AI affecting your day to day work in the insurance industry?” 38:21 “Is there a piece of career advice that’s been especially meaningful to you, whether it’s something that you’ve heard from a mentor or you’ve given this advice to other people?” 40:04 “How would you advise people to get domain expertise before they’ve gotten a chance to do a job in that industry?” 46:19 “Which skills would you say are evergreen irrespective of the tools that you’re using?” 47:51 “What are you learning about change management?” 49:31 “What does seeking mentorship mean for you?” 53:21 “Do you have any strategies or advice for keeping that statistical intuition sharp?” 54:16 “How do you partner with actuaries at work? Are there things that you need from the actuaries that make your job easier?”

Helpful links: Positron: https://posit.co/products/ide/positron/ Posit Workbench: https://posit.co/products/enterprise/workbench/

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 Dooti Roy, Head of Clinical Data Science Capability Management at Boehringer Ingelheim Pharmaceuticals, to chat about organizational change in data science, investing in internal open-source community, transitioning from SAS to R, and motivating long-term learning and adoption of new tools.

In this Hangout, we explore the instrumental role of internal community in driving organizational change. Dooti shared that during the preparation for the transformation process from closed source (like SAS) to R and open source, she was advised by Rachael Dempsey (creator of the DS hangout!) to invest in community and “don’t sleep on that.” Dooti reported that following this advice proved successful, as the internal community grew from the early adopters and became a safe space where colleagues help each other understand new concepts and overcome implementation challenges. This thriving community, which includes team members from the US, Europe, China, and Japan, serves as a springboard for testing new ideas, tools, and processes, generating global feedback that helps pull the institutional change forward.

Maybe our favorite part, Dootie shared that strategies like naming internal meetings “beginR” (for beginner office hours) help set the right expectation, ensuring people feel comfortable asking questions without feeling afraid of appearing naive.

Resources mentioned in the video and zoom chat: Positron Data Science Lab Session Registration → pos.it/dslab R/Pharma Conference Registration (Free Event) → https://rinpharma.com/ Community Building Tips & Tricks Site → https://pos.it/community-building Boehringer Ingelheim’s Open Source Davinci Modular Framework → https://github.com/Boehringer-Ingelheim/davinci

If you didn’t join live, one great discussion you missed from the zoom chat was about the struggle of finding time to learn new skills. Many attendees agreed that they are sooooo tired after work and that the learning often needs to be a work assignment to make time for it. This resonated with Dooti Roy’s observation that “I don’t have time” is one of the biggest pain points for colleagues attempting to learn new tools. Do you have the energy after work to do ambitious learning projects?

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Timestamps 00:00 Introduction 02:52 “What did organizational change look like and how did community help?” 06:19 “Do leaders understand the commitment to open source?” 15:25 “Was this your first time promoting open source?” 18:04 “What does data science look like at Boehringer Ingelheim?” 22:55 “How do you motivate long-term learning and development?” 31:05 “What is your costume for Halloween?” 31:55 “What is your team’s workflow and technology stack?” 44:50 “How do you motivate data professionals to document their code?” 48:40 “How do you encourage people to keep up with open source developments?”

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 Elliot Murphy, a VP of Engineering at Posit, to chat about engineering leadership philosophy, balancing maintenance versus innovation and risk, non-traditional career paths and the value of lifelong learning, and data science tool breakdowns including Posit Cloud, Posit Connect Cloud, and shinyapps.io.

In this Hangout, we explore some philosophical approaches to engineering and management, where Elliot stresses that focusing on people is more important than computers, and human relationships tend to outlast relationships with a given company or employer. Elliot discusses his role as primarily listening and synthesizing the brilliance of others, creating a supportive environment, and making space for people to take on risk and propose new ideas. He also highlighted the value of clear communication when addressing high-pressure environments (like when you’re sunsetting a software product).

Resources mentioned in the video and zoom chat: Cognition in the Wild (Book discussed regarding joint cognition) → https://mitpress.mit.edu/9780262581462/cognition-in-the-wild/ datapasta (R package) → https://github.com/MilesMcBain/datapasta AI Capabilities in Positron Workflow Demo → https://pos.it/workflow-demos

If you didn’t join live, one great discussion you missed from the zoom chat was about the surprising value and broad resources offered by local libraries, including free access to services like LinkedIn Learning, paid periodicals like the NY Times, and streaming platforms like Kanopy. Attendees praised libraries as the “best resource we hardly hear about” and key providers of freedom of information. Do you love your local library?!

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Timestamps: 00:00 Introduction 02:04 “Can you tell us a little bit about your journey to where you are?” 04:10 “What does a VP of engineering do? And what types of things are important to you from a philosophical standpoint for engineering and management?” 06:21 “What about your job lets you focus on the people?” 06:33 “Is there also a pressure to innovate?” 09:28 “How do you argue to leadership at a strategic level that that maintenance work is important to take up people’s time?” 11:48 “How do you balance engineers and data scientists wanting to incorporate best practices with fast prototyping?” 16:46 “What distinguishes science from engineering in data and also more broadly?” 18:28 “Any resources or any books that helped you bridge the gap between a non traditional background and your current position?” 23:00 “What is the secret to creating a good environment for the team?” 25:23 “Are there basics that you feel analysts or data scientists should be aware of in terms of engineering that would help their work?” 28:47 “How do you make decisions about when to either sunset a project or change directions?” 31:20 “What can those doing maintenance work do to add value to the organization to be safe from being displaced by automation?” 35:02 “What do you think many data scientists or analysts are missing about engineering infrastructure today that could simplify their day to day workflows?” 35:52 “How can a professional transition from a business intelligence role to a data scientist position?” 43:47 “What is your mantra or best practice to crack these professional certification exams?” 45:22 “Tell us the difference between Posit Cloud, Posit Connect Cloud, Posit Connect, and shinyapps.io.” 49:03 “How can a team avoid the trap of over-engineering?”

Additional resources: GitHub Repo for this Example: https://github.com/posit-dev/positron-ai-workshop Getting Started with Positron: Quick Tour: https://posit.co/resources/videos/get-started-with-positron-a-quick-tour-and-community-qa/ Introducing Databot (Blog Post): https://posit.co/blog/introducing-databot/ Posit AI Newsletter: https://posit.co/blog/2025-09-26-ai-newsletter/ Positron Assistant: https://positron.posit.co/assistant.html

https://positron.posit.co

Julia Silge

https://www.tidyverse.org/blog/2025/02/air/ https://github.com/posit-dev/air

Davis Vaughan, Lionel Henry

Follow along in the blog post: https://posit.co/blog/first-python-project-in-positron/

0:00 Introduction 0:19 Prerequisites 0:26: Create a workspace 1:28 Start project 2:40 Create a Quarto document 3:03 Load data 3:47 Visualize data 4:35 Use version control 5:40 Deploy to Posit Connect

Positron documentation: https://positron.posit.co Quarto documentation: https://quarto.org

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 Arcenis Rojas, Data Scientist at Indeed, to chat about econometrics, public vs private sector data science, navigating a varied career trajectory, AI integration in the hiring sphere, and making friends at conferences.

In this Hangout, Arcenis talked about how his career journey has been wide as opposed to vertically narrow. He shared that this breadth of experience has given him confidence that he can quickly figure out any dataset. He feels it also taught him how to communicate effectively about data to people at different levels and across various domains. He also shared his tech stack at Indeed, including RStudio, Positron, AWS, Snowflake, Quarto for reporting, Shiny for apps, and Posit Connect for deploying them.

An attendee asked about the impacts of AI on the job search space, and Arcenis shared the AI at Work Report (linked below) from the Indeed Hiring Lab. He says, based on research, generative AI is expected to assist many people but only replace small segments of the workforce in the coming 5-10 years, and that entry-level knowledge work is predicted to be the most highly impacted area.

Resources mentioned in the video and zoom chat: Indeed Hiring Lab: AI at Work Report 2025 → https://www.hiringlab.org/2025/09/23/ai-at-work-report-2025-how-genai-is-rewiring-the-dna-of-jobs/ To Explain or to Predict? (Galit Shmueli, 2010) → https://arxiv.org/abs/1101.0891 Announcing the 2025 table and plotnine contests → https://posit.co/blog/announcing-the-2025-table-and-plotnine-contests/

If you didn’t join live, one great discussion you missed from the zoom chat was about the wide variety of data types data scientists work with. Attendees shared that their data included genomics, finance/trading, environmental/natural resources, e-commerce products, and medical/clinical data. What kind of data types do you work with?

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Timestamps 00:00 Introduction 06:16 “What do you like to do for fun?” 08:51 “What are the unique aspects of financial and economic data science?” 15:07 “What are econometrics?” 16:02 “Is the difference that hard sciences stats is trying to explain what happened where econometrics might be what might happen in the future?” 19:39 “Suggestions for making data friends and going to a conference alone.” 23:26 “Do you see any misconceptions about the job market online, specifically the ATS thing?” 29:52 “How has your varied career trajectory been an advantage or a challenge in data science?” 34:08 “How is the recent hype wave of AI integration manifesting in the hiring sphere?” 40:08 “What are the tools that you use in your job for reporting?” 41:42 “How do you know when it is time to pivot and leave your role because your skills are stagnating?” 45:56 “How would you persuade leadership to use R or Python?” 49:32 “Did you find yourself always trying to use more complex models when simpler ones would serve the audience better?”

Learn more about Positron Assistant: https://positron.posit.co/assistant.html Sign up for our Workflow Demo on October 29, where we will demonstrate Positron Assistant: https://posit.co/workflow-demo/ai-powered-data-science-in-positron/

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 Dave Gruenewald, Senior Director of Data Science at Centene, to chat about polyglot teams, data science best practices, right-sizing development efforts, and process automation.

In this Hangout, we explore working in a polyglot team and fostering interoperability (a word that Libby loves, but struggles to pronounce out loud). Dave Gruenewald emphasizes that teams should use the tools they are comfortable with, whether that’s R or Python. Some strategies for collaboration across languages that Dave suggests include tools like Quarto to seamlessly run R and Python code in the same report. Teams utilize data science checkpoints, saving outputs as platform-agnostic file types like Parquet so that they can be accessed by any language. The use of REST APIs allows R processes to be accessed programmatically by Python (and vice versa), which can be a real game-changer. The newly released nanonext package was also highlighted as a promising development for improved interoperability.

Resources mentioned in the video and zoom chat: Posit Conf 2025 Table and Plotnine Contests → https://posit.co/blog/announcing-the-2025-table-and-plotnine-contests/ nanonext 1.7.0 Tidyverse Blog Post → https://www.tidyverse.org/blog/2025/09/nanonext-1-7-0/

If you didn’t join live, one great discussion you missed from the zoom chat was about pivoting away from academia, including leaving PhD programs. Many attendees shared their personal experiences of making the difficult decision to drop out of a PhD program. The community suggested alternative terms like “pivot,” “reallocating your resources,” or being a “refugee fleeing academia” instead of “drop out.” Dave Gruenewald shared that he himself left a PhD program but has “no regrets about that.” Did you leave a PhD program? You’re not alone!

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Thanks for hanging out with us!

Timestamps: 00:00 Introduction 02:21 “What types of data do your teams use?” 06:53 “Which of the three pillars you mentioned is your personal favorite to work on?” 09:26 “How do you avoid or divert scope creep?” 11:41 “How much of the project should be “planning” before any code happens?” 13:53 “Do you feel like people are just hopping in and going, hey, LLM, make me a POC?” 14:28 “Do you give them what they say they want, or do you give them what they need?” 16:40 “I’m wondering what public data do you wish existed?” 18:48 “Why not Positron yet?” 20:43 “How do you unify as a team and make it so that I can always read everybody else’s code?” 23:10 “Could you talk a little bit about how R and Python work together?” 27:28 “How to start package development with a team who are very new to package development.” 33:01 “What’s your greatest regret career wise?” 35:53 “What about your biggest wins, specifically in your early career?” 39:40 “How would you recommend building a data science culture and community from scratch?” 41:49 “Would you set a specific timeline for EDA, exploratory analysis, to scope the project better?” 45:15 “How do you define fun projects, and how much time do you allocate for exploration in those?” 48:21 “Does your team use DVC or something similar for data version control?” 50:00 “Can you talk a bit more about your pivot from academia into data science?” 51:31 “Any advice on where to look for opportunities in data science after getting a masters degree?”

Read the blog post: https://posit.co/blog/create-a-quarto-document-in-positron/

Resources Mentioned:

• Quarto in the Positron Guide: https://positron.posit.co/quarto.html • Getting Started with Quarto in Positron (R/Python): https://quarto.org/docs/get-started/hello/positron.html • Positron in the Quarto Guide: https://quarto.org/docs/tools/positron/

#Quarto #Positron #DataScience #QuartoTutorial #PositronIDE #DataVisualization #Publishing #RStats #Python #CodingWorkflow

Charlotte Wickham

• Positron - https://positron.posit.co/
• Positron Assistant - https://positron.posit.co/assistant.html

1. Getting Started with Positron (this recording)
2. AI-Powered Data Science in Positron: https://youtu.be/TrN-FMcOsOA?si=2nOb0q_nowMcS3xy
3. Take Positron to Work with Positron Pro: https://youtu.be/CNwZZvtAIEM

Helpful resources from this session:

1. Positron documentation: https://positron.posit.co/
2. Positron announcement (Why Positron & Why Now?): https://posit.co/blog/positron-product-announcement-aug-2025/
3. Positron Assistant and Databot announcement: posit.co/blog/positron-ai-product-announcement-aug-2025/
4. uv documentation: https://docs.astral.sh/uv/guides/install-python/
5. Git documentation: https://git-scm.com/downloads

Resources mentioned in the Q&A:

1. Exploratory Data Analysis with R in Positron: https://youtu.be/ndq2Mm3Dju8?feature=shared
2. Publishing from Positron: https://docs.posit.co/connect/user/publishing-positron-vscode/
3. For “very advanced users” regarding multi-root workspaces: https://code.visualstudio.com/docs/editing/workspaces/multi-root-workspaces
4. Great extension pack for Positron from Garrick: https://github.com/gadenbuie/positron-plus-1-e

posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Materials - https://github.com/juliasilge/get-unstuck-with-python posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Julia Silge

This presentation explores the complex and often contradictory nature of large language models (LLMs) in data science, acknowledging the simultaneous excitement and apprehension that we feel toward these technologies. We’ll provide a practical framework to help you understand the LLM ecosystem (from foundation models and hosting to SDKs and applications) that supports our current philosophy: augmenting, not replacing human intelligence. The talk demonstrates how Posit is addressing this space through two complementary approaches: building SDKs and tools that help you create your own LLM-powered solutions, and developing integrated LLM capabilities directly into data science workflows through tools like Positron assistant and databot. We’ll showcase practical, immediately useful applications while addressing current limitations, providing you with both the emotional preparation and technical foundation needed to effectively leverage LLMs in their data science practice today. posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Hadley Wickham, Joe Cheng

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Doing everything in one language is convenient but not always possible. For example, your Python app might need an algorithm only available as an R package. Or your R analysis might need to fit into a Python pipeline. What do you do? You take a polyglot approach! Many data scientists hesitate to explore beyond their main language, but combining R and Python can be powerful. In my talk, I’ll explain why polyglot data science is beneficial and address common concerns. Then, I’ll show you how to make it happen using tools like Quarto, Positron, Reticulate, and the Unix command line. By the end, you’ll gain a fresh perspective and practical ideas to start. posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Jeroen Janssens

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Carson Sievert, George Stagg, Tomasz Kalinowski, Winston Chang

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Slides - https://github.com/rstudio/rstudio-conf/blob/main/2025/jonathanmcpherson/10%20Years%20of%20Data%20Science%20Tools.key posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Materials - https://rlbarter.github.io/posit-conf-2025/#0 posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

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Once you start using Air, you’ll never worry about code style ever again! posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Davis Vaughan, Lionel Henry

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posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Inspecting raw data in data frames and tables can be a critical tool in the data preparation, tidying, and feature engineering process. In Positron, we made it a priority to design a modern Data Explorer component that works well for both large and small datasets. In this talk, I will discuss the design of the Data Explorer UI and its backends for Python, R, and DuckDB, and how we made it work smoothly with massive datasets having millions of rows or thousands of columns. Additionally, I will discuss the sorting, filtering, search, and statistical data visualization capabilities that we have added to help make users more productive. posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

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Understanding these trade-offs helps you find the best fit. By the end of the session, you’ll have a clear framework for choosing the right IDE for your data science and analytics tasks. posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Isabel Zimmerman

Materials - https://github.com/austin3dickey/ssh-demo posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Data science is full of complex topics—Bayesian statistics, neural networks, databases, and more. Now, imagine teaching one of these to a baby. What would you say? How would you say it? This exercise highlights the power of simplification: anyone can teach, and anyone can learn. Breaking down complexity makes data science accessible, impactful, and fosters greater creativity and flexibility. In this talk, I’ll share my approach to simplifying data science education with a playful demonstration using Posit’s new IDE, Positron, as the focus! posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

Materials - https://github.com/sharon-wang/positron-tips-and-tricks posit::conf(2025)

Subscribe to posit::conf updates: https://posit.co/about/subscription-management/

• Positron documentation: https://positron.posit.co/
• Download Positron: https://positron.posit.co/download.html
• Setting up Python in Positron: https://positron.posit.co/python-installations.html
• Setting up Positron Assistant: https://positron.posit.co/assistant.html
• GitHub repository: https://github.com/posit-marketing/streamlit-example
• Blog post: https://posit.co/blog/streamlit-in-positron/
• UV: https://docs.astral.sh/uv/
• Kyle Walker’s “Distance and proximity analysis in Python” tutorial: https://walker-data.com/posts/proximity-analysis/

Keywords: Positron, Streamlit, Streamlit deployment, Positron platform, web application, data app, data science, Python, IDE, integrated development environment, Streamlit for beginners, build a web app, interactive apps, Python programming, data analysis, how to use Positron, Streamlit on Positron

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:

• 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.

• 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!

• 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.

• 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!

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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?”

Jenny Bryan

Positron documentation: https://positron.posit.co/ Download Positron: https://positron.posit.co/download.html Read the blog post: https://posit.co/blog/eda-in-positron

Air documentation: https://posit-dev.github.io/air/

Mine Çetinkaya-Rundel

Additional Material or Paper *Visit https://positron.posit.co for documentation and installers *Find us on GitHub at https://github.com/posit-dev/positron *Positron is currently available on Posit Workbench in preview

Julia Silge

Positron Documentation: https://positron.posit.co/ Download Positron: https://positron.posit.co/download.html Read the blog post: https://posit.co/blog/a-quick-tour-of-positron

• Posit Conf https://posit.co/conference/
• The Test Set https://thetestset.co
• Positron https://positron.posit.co
• Python for Data Analysis, 3E https://wesmckinney.com/book/
• Python Polars: The Definitive Guide https://polarsguide.com
• Code produced during the session https://github.com/jeroenjanssens/pydytuesday-uncut/blob/main/session-03/github.py

#polars #pydytuesday #datascience

Jeroen Janssens

Databricks Named a Leader in the 2025 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms: https://www.databricks.com/blog/databricks-named-leader-2025-gartner-magic-quadrant-data-science-and-machine-learning Build and deploy quality AI agent systems: https://www.databricks.com/product/artificial-intelligence See all the product announcements from Data + AI Summit: https://www.databricks.com/events/dataaisummit-2025-announcements

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

• Weekly US Gas Prices https://github.com/rfordatascience/tidytuesday/blob/main/data/2025/2025-07-01/readme.md
• Code produced during the session https://github.com/jeroenjanssens/pydytuesday-uncut/
• Plotnine https://plotnine.org
• Positron https://positron.posit.co

#python #polars #tidytuesday #datascience

Jeroen Janssens, Michael Chow

Learn more about the Databricks and Posit partnership by exploring the partnership page and resources: https://posit.co/use-cases/databricks/

• Code produced during the session: https://github.com/jeroenjanssens/pydytuesday-uncut/blob/main/2025-06-17/01-start.py
• PydyTuesday https://github.com/posit-dev/pydytuesday
• TidyTuesday https://github.com/rfordatascience/tidytuesday
• Getting Data from the TidyTuesday Repo with Python https://www.youtube.com/watch?v=ol2FrSL5gVU
• Positron IDE https://positron.posit.co
• Data Science at the Command Line https://jeroenjanssens.com/dsatcl/
• Python Polars: The Definitive Guide https://polarsguide.com
• Polars https://pola.rs
• Plotnine https://plotnine.org
• Great Tables https://posit-dev.github.io/great-tables/
• The Big Year https://www.imdb.com/title/tt1053810/

00:00 Introduction 02:46 Getting the data with uv 13:18 Positron IDE 17:42 Importing Polars 23:17 Plotting a bar chart with Plotnine 33:55 Inspecting duplicates 46:30 Handling missing values 58:56 Crafting a great table 1:38:48 Reflection

Jeroen Janssens, Michael Chow

To join future data science hangouts, add it to your calendar here: https://pos.it/dsh - All are welcome! We’d love to see you! Thursdays at 12PM US Eastern

We were recently joined by upcoming Posit Conf 2025 keynote speakers Kieran Healy, Professor of Sociology at Duke University, and Jonathan McPherson, Software Architect at Posit PBC, to chat about how and why open-source IDEs like RStudio and Positron get made, how to do data visualization for discovery and explanation, what their keynotes are going to be about, and what’s next for Posit’s IDE development, including AI integration.

In this Hangout, Kieran talked about the trustworthy data visualization. He highlighted that while data visualization is a powerful way to condense and present information, often creating compelling and authoritative artifacts, phrases like “visual storytelling” can be problematic if they encourage presenting a predetermined narrative not fully supported by data. He emphasized that the trustworthiness of visualizations does not come solely from the techniques used or the software, but from a “web of social processes and individual commitments” that cannot be easily automated.

Jonathan talked about the future of Positron and its relationship with RStudio, addressing whether Positron is intended to replace RStudio. He clarified that the long-term goal for Positron is to make it the best Integrated Development Environment (IDE) for working with data in any language. He explained that Positron is built with an extensibility layer, allowing anyone to write plugins for new languages or capabilities, making it a robust and evolving data science workbench. It does not have all of RStudio’s features and makes different design trade-offs. RStudio, having evolved over decades, is highly optimized for specific R-based workflows and remains the best at what it does for those use cases.

Resources mentioned in the video and zoom chat: Posit Conference 2025 Registration → https://posit.co/conference/ Kieran Healy’s Website → https://kieranhealy.org Kieran Healy’s book “The Ordinal Society” → https://theordinalsociety.com/ Kieran Healy’s book “Data Visualization: A Practical Introduction” → https://socviz.co/ Jonathan McPherson’s LinkedIn → https://www.linkedin.com/in/jonathanmcpherson Joe Cheng’s AI Talk on Harnessing LLMs for Data Analysis → https://youtu.be/owDd1CJ17uQ?feature=shared TidyTuesday GitHub → https://github.com/rfordatascience/tidytuesday Positron IDE → https://positron.posit.co/ Will R Chase’s talk on making clear plots → https://www.youtube.com/watch?v=h5cTacaWE6I

If you didn’t join live, one great discussion you missed from the zoom chat was about the ongoing debate and practical tips for moving from presenting tables of numbers to visualizations. Community members shared various strategies, including using color-mapped tables as an intermediate step, providing both tables and visuals, and ensuring accessibility and interpretability for diverse audiences. Are you team tables or team graphs?

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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!

Joe Cheng

TidyTuesday GitHub Repo: https://github.com/rfordatascience/ti … Posit PydyTuesday GitHub Repo: https://github.com/posit-dev/python-t … TidyTuesday hashtag search on Bluesky: https://bsky.app/search?q=tidytuesday Other videos in this PydyTuesday playlist: • PydyTuesday | Python How-to Videos

#pythoncontent

TidyTuesday GitHub Repo: https://github.com/rfordatascience/ti … Posit PydyTuesday GitHub Repo: https://github.com/posit-dev/python-t … TidyTuesday hashtag search on Bluesky: https://bsky.app/search?q=tidytuesday Other videos in this PydyTuesday playlist: • PydyTuesday | Python How-to Videos

#pythoncontent

TidyTuesday GitHub Repo: https://github.com/rfordatascience/ti … Posit PydyTuesday GitHub Repo: https://github.com/posit-dev/python-t … TidyTuesday hashtag search on Bluesky: https://bsky.app/search?q=tidytuesday Other videos in this PydyTuesday playlist: • PydyTuesday | Python How-to Videos

#pythoncontent

• TidyTuesday GitHub Repo: https://github.com/rfordatascience/tidytuesday
• Posit PydyTuesday GitHub Repo: https://github.com/posit-dev/python-tidytuesday
• TidyTuesday hashtag search on Bluesky: https://bsky.app/search?q=tidytuesday
• Other videos in this PydyTuesday playlist: https://www.youtube.com/playlist?list=PL9HYL-VRX0oSDQjicFMLIIdcLv5NuvDp9

#pythoncontent

Documentation mentioned: Positron, next-generation data science IDE built by Posit: https://positron.posit.co/ Quarto tabset documentation: https://quarto.org/docs/output-formats/html-basics.html#tabset-groups

Packages / Extensions mentioned: Pins: https://pins.rstudio.com/ Vetiver: https://vetiver.posit.co Orbital: https://orbital.tidymodels.org Elmer: https://elmer.tidyverse.org Tabby Extension: https://quarto.thecoatlessprofessor.com/tabby/

Blog posts: AI chat apps with Shiny for Python: https://shiny.posit.co/blog/posts/shiny-python-chatstream/ Using an LLM to enhance a data dashboard written in Shiny: R Sidebot & Python Sidebot Marco Gorelli Data Science Hangout (polars): https://youtu.be/lhAc51QtTHk?feature=shared Emily Riederer’s blog post on Polars: https://www.emilyriederer.com/post/py-rgo-polars/ Jeffrey Sumner’s tabset example: https://rpy.ai/posts/visualizations%20with%20r%20and%20python/r_python_visualizations Emily Riederer’s blog post on Python and R ergonomics: https://www.emilyriederer.com/post/py-rgo/11 Sam Tyner’s blog post on Lessons from “Tidy Data”: https://medium.com/@sctyner90/10-lessons-from-tidy-data-on-its-10th-anniversary-dbe2195a82b7

Other: Hadley Wickham’s cocktails website: https://cocktails.hadley.nz 5 Posit subscription management to find out about new tools, events, etc.: https://posit.co/about/subscription-management/

New to Posit? Posit builds enterprise solutions and open source tools for people who do data science with R and Python. (We are also the company formerly called RStudio) We’d love to have you join us for future community events!

Every Thursday from 12-1pm ET we host a Data Science Hangout with the community and invite you to join us! You can add that event to your calendar with this link: https://www.addevent.com/event/Qv9211919

Hadley Wickham

www.pydata.org

The process of data science is inherently iterative, requiring constant inspection and visualization of data. Positron is a new, next generation integrated development environment (IDE) built to facilitate exploratory data analysis, reproducible authoring, and publishing data artifacts. This talk will discuss the motivation behind creating Positron and demonstrate the features that support these iterative data science workflows.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Isabel Zimmerman

Slide deck 1: https://speakerdeck.com/juliasilge/introducing-positron Slide deck 6: https://speakerdeck.com/jennybc/positron-for-r-and-rstudio-users

Davis Vaughan, Isabel Zimmerman, Jenny Bryan, Julia Silge, Lionel Henry

Watch the full interview “817: The Positron IDE, Tidy NLP and MLOps — with Dr. Julia Silge” here: https://www.superdatascience.com/817

Julia Silge

This episode is brought to you by Gurobi (https://www.gurobi.com/personas/optimization-for-data-scientists/) , the Decision Intelligence Leader, and by ODSC (https://odsc.com/california) , the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn: • [00:00:00] Introduction • [00:03:23] Overview of Posit and Positron IDE • [00:08:33] How the needs of a data scientist differ from those of a software developer • [00:17:56] How to contribute to the open-source Positron • [00:34:52] MLOps and Vetiver: Tools for deploying and maintaining ML models • [00:48:34] Natural Language Processing (NLP) and the Tidyverse approach • [01:22:18] The role of AI and LLMs in data science education

Additional materials: https://www.superdatascience.com/817

Julia Silge

https://quarto.org/docs/get-started/

Timestamps: 0:00 Introduction 0:41 Quarto is an open-source, scientific and technical publishing system 1:22 Computational documents and scientific markdown made easy for single source publishing 3:08 How to use Quarto 4:24 Quarto works with VS Code, Positron, Jupyter, & RStudio 5:22 Quarto’s multi-language workflow 7:21 Quarto syntax 8:40 Quarto formats (html, pdf, docx, typst, beamer, pptx, revealjs, etc.) 12:19 HTML Theming 14:10 Typst CSS for nice table output in PDF 16:24 Publishing (Quarto Pub, GitHub Pages, Posit Connect, Posit Cloud, Netlify, Confluence, Hugging Face, etc.) 17:36 Shortcodes 19:10 Quarto Extensions 19:49 Quarto Projects 22:53 Project configuration examples for a website and a book 23:42 Resources to get started!

Christophe Dervieux