Podcasts about RStudio

House Keeping Google / YouTube Update Join the Discord! Feedback Rust in the Linux Kernel. R Stuff What is R Again? Great presentation by John Chambers at UseR! 2006 https://www.r-project.org/conferences/useR-2006/Slides/Chambers.pdf The times have changed, now R is very much suited for production use and not just an academic research language Highly recommend reading Advanced R for more comprehensive details on the quirks of the language https://adv-r.hadley.nz/index.html R VS Python for Data? Different philosophies on the use of the language CRAN vs PyPi Interoperability becoming more mainstream now Visualization: R has always been leaps and bounds ahead (Grammar of Graphics, interactive widgets, etc) R Dev Stack? IDEs: RStudio, now Positron https://positron.posit.co/ Managing package installations with renv https://rstudio.github.io/renv/ Building web apps with Shiny: https://shiny.posit.co/ (I got so engrossed in this space that I created the Shiny Developer Series because of it) Early adopter of using Docker with R in devcontainers with VS-Code. New tech I'm excited about to enhance dev stacks and sharing apps WebAssembly with webR https://docs.r-wasm.org/webr/latest/ Shiny apps in webR? Yes you can https://github.com/RConsortium/submissions-pilot4-webR Managing dev environment combined with Nix: The rix package https://github.com/ropensci/rix (More organized links for show notes) R Language: https://r-project.org Posit (formerly RStudio): https://posit.co RStudio IDE https://posit.co/products/open-source/rstudio/ Positron (still in beta): https://positron.posit.co/ History of S and R presentation by John Chambers at useR! 2006: http://www.r-project.org/user-2006/Slides/Chambers.pdf Advanced R (2nd edition) by Hadley Wickham https://adv-r.hadley.nz/index.html Shiny - Easy interactive web applications with R: https://shiny.posit.co/ renv - Project environments for R: https://rstudio.github.io/renv/ R Markdown: https://rmarkdown.rstudio.com/ WebR - R in the browser: https://docs.r-wasm.org/webr/latest/ Rix - Reproducible Data Science environments for R with Nix: https://github.com/ropensci/rix Chromatic by ModRetro Chromatic: https://modretro.com/products/chromatic-tetris-bundle?variant=47637522579758 FPGA Mike's Review Eric's Thoughts Eric's Socials R Weekly Highlights: https://serve.podhome.fm/r-weekly-highlights Shiny Developer Series: https://shinydevseries.com/ R Podcast: https://r-podcast.org Bluesky: @rpodcast@bsky.social Mastodon: @rpodcast@podcastindex.social LinkedIn: https://www.linkedin.com/in/eric-nantz-6621617/ Coder's Socials Mike on X (https://x.com/dominucco) Mike on BlueSky (https://bsky.app/profile/dominucco.bsky.social) Coder on X (https://x.com/coderradioshow) Coder on BlueSky (https://bsky.app/profile/coderradio.bsky.social) Show Discord (https://discord.gg/k8e7gKUpEp) Alice (https://alice.dev)

In this episode, I'm joined by JJ Allaire, founder and executive chairman at Posit, and Carlos Scheidegger, a software engineer at Posit, to explore Quarto, an open-source tool revolutionizing technical publishing. We discuss how Quarto empowers users to seamlessly transform Jupyter notebooks into polished reports, dashboards, e-books, websites, and more. JJ shares his journey from creating RStudio to developing Quarto as a versatile, multi-language tool, while Carlos delves into its roots in reproducibility and the challenges of academic publishing. Don't miss this deep dive into a tool that's shaping the future of data-driven storytelling! Episode sponsors Talk Python Courses DigitalOcean Links from the show JJ Allaire JJ on LinkedIn: linkedin.com JJ on GitHub: github.com Carlos Scheidegger Personal site: cscheid.net Mastodon: @scheidegger Fast AI: fast.ai nbdev: nbdev.fast.ai nbsanity - Share Notebooks as Polished Web Pages in Seconds: answer.ai Pandoc: pandoc.org Observable: github.com Quarto Pub: quartopub.com Deno: deno.com Real World Data Science site: realworlddatascience.net Typst: typst.app Github Actions for Quarto: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to Talk Python on YouTube: youtube.com Talk Python on Bluesky: @talkpython.fm at bsky.app Talk Python on Mastodon: talkpython Michael on Bluesky: @mkennedy.codes at bsky.app Michael on Mastodon: mkennedy

Context is king in a trifecta of R packages harnessing LLMs to be your virtual assistant in package development and data science, plus the world (of data) is at your fingertips for data exploration and sharing your insights using the innovative closeread Quarto extension.Episode LinksThis week's curator: Jonathan Kitt - @jonathankitt.bsky.social (Bluesky)Three experiments in LLM code assist with RStudio and PositronGapminder: how has the world changed?Downloading datasets from Our World in Data in REntire issue available at rweekly.org/2025-W06Supplement ResourcesFrom hours to minutes: accelerating your tidymodels code https://youtu.be/pTMiDHFIiPQ?si=4qZC3_NLUVhD5hAaEffecient Machine Learning with R https://emlwr.org/Closeread: Bringing scrollytelling to Quarto https://youtu.be/KqLxy66B3lQ?si=w7DIB4QhYk2u6cLGCloseread Posit contest submissions https://forum.posit.co/tag/closeread-prize-2024Extract Information From Images and PDFs With R & LLMs https://3mw.albert-rapp.de/p/extract-information-from-images-and-pdfs-with-r-llmsusgs geological survey mapping water https://waterdata.usgs.gov/blog/acs-maps/Supporting the showUse the contact page at https://serve.podhome.fm/custompage/r-weekly-highlights/contact to send us your feedbackR-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby, and then head over to the R-Weekly Highlights podcast entry on the index.A new way to think about value: https://value4value.infoGet in touch with us on social mediaEric Nantz: @rpodcast@podcastindex.social (Mastodon), @rpodcast.bsky.social (BlueSky) and @theRcast (X/Twitter)Mike Thomas: @mike_thomas@fosstodon.org (Mastodon), @mike-thomas.bsky.social (BlueSky), and @mike_ketchbrook (X/Twitter) Music credits powered by OCRemixCosta del Sol DANCE - Final Fantasy VII - posu yan - https://ocremix.org/remix/OCR00095Aerobotics - Mega Man 8 - Just Coffee - https://ocremix.org/remix/OCR03323

Guest Alison Hill Panelist Richard Littauer Show Notes We're kicking off the new year of Sustain with host Richard Littauer discussing sustaining open source software with guest, Alison Hill, VP of Product at Anaconda, and a cognitive scientist with a PhD in psychology. Alison shares her journey from academia to industry, emphasizing the importance of statistics and data science in her career. She explains her role at Anaconda, focusing on developing secure and compatible distribution of Python packages and managing the community repository, Anaconda.org. The conversation covers the significance of product management in open source projects, particularly those with corporate backing, and how these roles can help in balancing user needs and business goals. In addition, Alison shares her thoughts on the challenges and strategies for maintaining open source projects without corporate support and touches on the ‘palmer penguins' project. Click to download now! [00:01:13] Alison discusses her transition from academic research in cognitive science to industry and data science, emphasizing her passion for statistics and education. [00:02:41] Alison explains her work at Anaconda, focusing on product management and the Anaconda distribution, aiming to ease the use of Python and R packages in the industry and academia. She also elaborates on other projects she oversees, including Anaconda.org and its role in supporting open source projects and enterprise needs. [00:05:17] We hear how Anaconda sustains itself financially through enterprise offerings and the balance of supporting open source while maintaining a business model. [00:07:14] Alison shares her previous experience as the first PM of data science communication at Posit (formerly RStudio) and her role in enhancing data science education and product development. [00:12:49] Richard and Alison explore the challenges of sustaining open source projects without corporate backing and strategies for maintaining personal and project health in the open source community. Alison discusses common mistakes companies make by confusing project management with product management in open source projects. [00:17:18] Richard asks about the skills needed for developers to adopt a product-oriented approach. Alison suggests that successful product-oriented developers often have high empathy for end-users and experience with the pain points at scale, which helps them anticipate and innovate solutions effectively. [00:20:49] Richard expresses concerns about the sustainability of smaller, community-led open source projects that lack corporate backing and the structured support that comes with it. Alison acknowledges her limited experience with non-corporate open source projects but highlights the difficulty in maintaining such projects without institutional support, and she shares her personal challenges with keeping up with open source project demands. [00:27:41] Alison stresses the importance of clear goals and understanding the implications of joining larger ecosystems, reflects on the need for clarity about the desired outcomes when joining larger ecosystems, and shares examples of successful and unsuccessful engagements in such settings. [00:29:52] She discusses alternative sustainability models, including paid support and subscriptions. [00:33:00] Alison brings up the example of Apache Arrow and the challenges it faced with corporate sponsorship. [00:34:23] We wrap up with Richard acknowledging that not all open source projects require significant funding or formal business models, and Alison explains the ‘palmerpenguins' project she did at the beginning of COVID. [00:37:07] Find out where you can follow Alison on the web. Quotes [00:22:18] “What is the minimum level of support you need to not feel like you're drowning?” Spotlight [00:38:14] Richard's spotlight is Bernard Cornwell. [00:38:39] Alison's spotlight is the book, Impossible Creatures. Links SustainOSS (https://sustainoss.org/) podcast@sustainoss.org (mailto:podcast@sustainoss.org) richard@sustainoss.org (mailto:richard@sustainoss.org) SustainOSS Discourse (https://discourse.sustainoss.org/) SustainOSS Mastodon (https://mastodon.social/tags/sustainoss) Open Collective-SustainOSS (Contribute) (https://opencollective.com/sustainoss) Richard Littauer Socials (https://www.burntfen.com/2023-05-30/socials) Alison Hill, PhD Website (https://www.apreshill.com/) Alison Presmanes Hill, PhD LinkedIn (https://www.linkedin.com/in/apreshill/) Alison Presmanes Hill GitHub (https://github.com/apreshill) Anaconda (https://www.anaconda.com/) Anaconda.org (https://anaconda.org/) The Third Bit-Dr. Greg Wilson (https://third-bit.com/about/) Sustain Podcast-Episode 64: Travis Oliphant and Russel Pekrul on NumPy, Anaconda, and giving back with FairOSS (https://podcast.sustainoss.org/guests/oliphant) Intercom on Product Management (https://www.intercom.com/resources/books/intercom-product-management) Sustain Podcast-Episode 135: Tracy Hinds on Node.js's CommComm and PMs in Open Source (https://podcast.sustainoss.org/135) Hadley Wickham (https://en.wikipedia.org/wiki/Hadley_Wickham) palmerpenguins-GitHub (https://allisonhorst.github.io/palmerpenguins/articles/intro.html) Bernard Cornwell (https://en.wikipedia.org/wiki/Bernard_Cornwell) Impossible Creatures by Katherine Rundell (https://www.penguinrandomhouse.com/books/743371/impossible-creatures-by-katherine-rundell-illustrated-by-ashley-mackenzie/) Credits Produced by Richard Littauer (https://www.burntfen.com/) Edited by Paul M. Bahr at Peachtree Sound (https://www.peachtreesound.com/) Show notes by DeAnn Bahr Peachtree Sound (https://www.peachtreesound.com/) Special Guest: Alison Hill.

The future of R-Universe looks even brighter for 2025 and beyond, revisiting the key factors for possibly switching to the Positron IDE, and why there is more than meets the eyes when it comes to the potential of LLMs and AI (even in highly-regulated industries).Episode LinksThis week's curator: Eric Nantz - @rpodcast@podcastindex.social (Mastodon), @rpodcast.bsky.social (BlueSky), and @theRcast (X/Twitter)R-Universe Named R Consortium's Newest Top Level ProjectPositron vs RStudio - is it time to switch?Summer is Coming: AI for Shiny, R, and PharmaEntire issue available at rweekly.org/2024-W50Supplement ResourcesrOpenSci Blog Post https://ropensci.org/blog/2024/12/03/r-universe-r-consortium-tlp/Positron IDE - A new IDE for data science https://drmowinckels.io/blog/2024/positron/Fun with Positron https://www.andrewheiss.com/blog/2024/07/08/fun-with-positron/Open VSX Registry https://open-vsx.orgPower Mode Extension https://open-vsx.org/extension/hoovercj/vscode-power-modeJoe Cheng's slides from R/Pharma keybote https://jcheng5.github.io/pharma-ai-2024/#/title-slideR Consortium Submissions Pilot 2 Shiny Application https://github.com/RConsortium/submissions-pilot2Daniel Sebanes Bove & Joe Cheng - Discussion of R/Pharma Keynote https://youtu.be/AU1MmcXYnJ0?si=A3V9JHYdZLiz-lvvPractical Tips for Using Generative AI in Data Science Workflows https://youtu.be/rPeOdc8jTSE?si=APtIhpRqlh2I_Ek1Apple Music Wrapped in R https://www.andrewheiss.com/blog/2024/12/04/apple-music-wrapped-r/Predicting Best Picture at the 2025 Academy Awards https://www.markhw.com/blog/oscars2025Navidrome - Your Personal Streaming Service https://www.navidrome.org/Scrubbing your music with Maloja https://wenkdth.org/posts/maloja-scrobbling/Supporting the showUse the contact page at https://serve.podhome.fm/custompage/r-weekly-highlights/contact to send us your feedbackR-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby, and then head over to the R-Weekly Highlights podcast entry on the index.A new way to think about value: https://value4value.infoGet in touch with us on social mediaEric Nantz: @rpodcast@podcastindex.social (Mastodon), @rpodcast.bsky.social (BlueSky) and @theRcast (X/Twitter)Mike Thomas: @mike_thomas@fosstodon.org (Mastodon), @mike-thomas.bsky.social (BlueSky), and @mike_ketchbrook (X/Twitter) Music credits powered by OCRemixThe Traveling Band's Last Song - Wild Arms: Armed and Dangerous - Artem Bank - https://ocremix.org/remix/OCR02588Secrets Abound - Final Fantasy - Midgarian Sky - https://ocremix.org/remix/OCR02452

Send us a textOver the past few years, a dedicated team has been immersed in building a Generative AI startup @ HAL9 The journey has been a masterclass in innovation, resilience, and learning. Some strategies paid off immensely (enter ChatGPT productivity hacks), while others served as hard-earned lessons about the dangers of over-investing in the wrong initiatives.To share these insights, an upcoming webinar with Javier Luraschi will focus purely on learning—no sales pitches, just real-world experiences. It will explore the highs, lows, and everything in between of AI product development, offering practical takeaways for teams and creators navigating this space.Key topics include:1️⃣ AI Productivity Hacks – How tools like ChatGPT have redefined work efficiency.2️⃣ Product Development Wins & Fails – The costly missteps to avoid and strategies that led to breakthroughs.3️⃣ Creative AI Tools – Evaluating tools like MidJourney, Flux, and others: the game-changers vs. the underwhelming.This session is designed for anyone looking to maximise their AI tools, refine product strategies, and learn from the lived experiences of others in the field.Javier Luraschi is a software engineer with experience in technologies ranging from desktop, web, mobile and backend, to augmented reality and deep learning applications. He is currently the founder of Hal9 Inc, a Seattle-based company dedicated to making Artificial Intelligence truly accessible. He previously worked for RStudio, Microsoft Research and SAP and holds a double degree in Mathematics and Software Engineering. Javier is the author of various R packages like sparklyr, mlflow, r2d3, and torch.Thank you to our Community PatronsVisAgiChange AngelsBusinessmap Formerly KanbanizeWomen in Technology and Science Ireland Find us here: www.agileleanireland.org

How can artificial intelligence simplify your daily work? How do tools like GitHub Copilot streamline tasks for statisticians and data scientists? In this episode of The Effective Statistician, I explore these questions with Paolo Eusebi, who shares his direct experience using Copilot in R Studio. We dive into how AI can suggest accurate code, assist with data manipulation, and help you quickly learn new programming techniques. We also discuss the critical need to safeguard data privacy when using these tools in larger organizations. Join us to see how AI can boost your productivity and transform how you work!

Win 10 fix, R-Studio, Wintoys, Bulk Crap Uninstaller

Open access software tools like ODK (Open Data Kit) have been a game changer in enabling access to digital data collection. Lucie and David discuss what makes ODK so interesting, and compare its development and use to that of R-Studio, another open access software that has made waves in data analysis. What will be the next step change in data collection? Does ODK's impact represent an alternative model to that of “big bets” as the route to bring about large-scale change?

https://youtu.be/bC1dPevezMU Download as MP3 (https://aphid.fireside.fm/d/1437767933/32f28071-0b08-4ea1-afcc-37af75bd83d6/9e665ee3-9e75-4e49-b902-3e5c04e45f34.mp3) Sponsored by LINBIT: Visit destinationlinux.net/linbit (https://destinationlinux.net/linbit) to learn how LINBIT's OSS, based on DRBD® and LINSTOR®, can be used for Kubernetes, CloudStack, OpenNebula, and more. Support the show by becoming a patron at tuxdigital.com/membership (https://tuxdigital.com/membership) or get some swag at tuxdigital.com/store (https://tuxdigital.com/store) Hosted by: Michael Tunnell = michaeltunnell.com (https://michaeltunnell.com) Ryan DasGeek = dasgeek.net (https://dasgeek.net) Jill Bryant = jilllinuxgirl.com (https://jilllinuxgirl.com) Chapters: 00:00:00 Intro 00:00:47 Community Feedback 00:10:47 Sponsored by LINBIT 00:12:06 Antivirus on Linux, do we need it? 00:31:28 Linux is getting an ARM laptop too 00:49:15 Gaming: Containment Zone 00:52:15 Software Spotlight: Encrypted Notepad 2 00:56:46 Tip of the Week: R, RStudio & officerR for powerpoint files 01:09:01 Outro Links: Community Feedback https://radxa.com/products (https://radxa.com/products) https://destinationlinux.net/comments (https://destinationlinux.net/comments) Antivirus on Linux, do we need it? (Kaspersky Virus Removal Tool) https://usa.kaspersky.com/blog/kvrt-for-linux/30182/ (https://usa.kaspersky.com/blog/kvrt-for-linux/30182/) https://www.clamav.net/ (https://www.clamav.net/) https://www.comodo.com/home/internet-security/antivirus-for-linux.php (https://www.comodo.com/home/internet-security/antivirus-for-linux.php) Linux is getting an ARM laptop too (thanks Tuxedo Computers) https://liliputing.com/schenker-shows-off-a-linux-laptop-prototype-with-snapdragon... (https://liliputing.com/schenker-shows-off-a-linux-laptop-prototype-with-snapdragon-x-elite-at-computex-2024/) https://www.techpowerup.com/323119/schenker-xmg-at-computex-2024-evo-14... (https://www.techpowerup.com/323119/schenker-xmg-at-computex-2024-evo-14-and-evo-15-qualcomm-powered-tuxedo) Containment Zone https://store.steampowered.com/app/2279490/Containment_Zone/ (https://store.steampowered.com/app/2279490/Containment_Zone/) Encrypted Notepad https://github.com/ivoras/EncryptedNotepad2 (https://github.com/ivoras/EncryptedNotepad2) https://www.helpnetsecurity.com/2024/05/31/encrypted-notepad-open-source... (https://www.helpnetsecurity.com/2024/05/31/encrypted-notepad-open-source-text-editor/) R, RStudio & officerR for powerpoint files https://posit.co/download/rstudio-desktop/ (https://posit.co/download/rstudio-desktop/) https://davidgohel.github.io/officer/ (https://davidgohel.github.io/officer/) Also check out https://www.youtube.com/@dasgeek (https://www.youtube.com/@dasgeek) https://tuxdigital.com (https://tuxdigital.com) Encrypted Notepad instructions: First make sure the Go 1.22+ library is installed. Then run the following commands from terminal: git clone https://github.com/ivoras/EncryptedNotepad2.git cd EncryptedNotepad2 go build ./EncryptedNotepad2

Another way to hop on LLM train with the chattr package, a clever use of defensive programming to get to those warnings in your tests faster, and a major milestone for the R-Hub project.Episode LinksThis week's curator: Tony Elhabr - @tonyelhabr@skrimmage.com (Mastodon) & @TonyElHabr (X/Twitter)Chat with AI in RStudioTest warnings fasterR-hub v2Entire issue available at rweekly.org/2024-W16Supplement ResourcesR/Pharma 2023 presentation by Edgar Ruiz (GitHub Copilot in RStudio) - https://youtu.be/-Fjb8LZmTSIThe 2024 Appsilon Shiny Conference is just days away! https://www.shinyconf.com/Supporting the showUse the contact page at https://rweekly.fireside.fm/contact to send us your feedbackR-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby, and then head over to the R-Weekly Highlights podcast entry on the index.A new way to think about value: https://value4value.info Get in touch with us on social media Eric Nantz: @rpodcast@podcastindex.social (Mastodon) and @theRcast (X/Twitter) Mike Thomas: @mikethomas@fosstodon.org (Mastodon) and @mikeketchbrook (X/Twitter) Music credits powered by OCRemixMemories of a Master - Street Fighter II: The World Warrior - Captain Hogan - https://ocremix.org/remix/OCR02268Higgins Goes to Miami - Adventure Island - virt - https://ocremix.org/remix/OCR00461

How a recent pivot in one of the most popular testing frameworks in R unlocks mocking once again, bringing robust grammar checks to your R development environment with rspell, and flex your Shiny and HTML design muscles with flexbox. Episode Links This week's curator: Batool Almarzouq - @batool664 (https://twitter.com/batool664) (X/Twitter) Update on mocking for testing R packages (https://blog.r-hub.io/2024/03/21/mocking-new-take/) {rspell} (https://rfsaldanha.github.io/rspell/) Are you writing in a foreign language? The RStudio spelling dictionary setting is not sufficient to correct grammar errors. Try the {rspell} package to grammar-proof your notebooks and documentation straight on RStudio without copying-pasting. 3MW (Aligning content with flexboxes) (https://3mw.albert-rapp.de/p/weather-ui-flexbox) Entire issue available at rweekly.org/2024-W13 (https://rweekly.org/2024-W13.html) Supplement Resources testthat 3.2.0 re-introduced mocking after it was removed in 2019. The PR with Hadley's commentary https://github.com/r-lib/testthat/pull/1739#issuecomment-1428027869 Supporting the show Use the contact page at https://rweekly.fireside.fm/contact to send us your feedback R-Weekly Highlights on the Podcastindex.org (https://podcastindex.org/podcast/1062040) - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby (https://getalby.com/), and then head over to the R-Weekly Highlights podcast entry on the index. A new way to think about value: https://value4value.info Get in touch with us on social media Eric Nantz: @rpodcast@podcastindex.social (https://podcastindex.social/@rpodcast) (Mastodon) and @theRcast (https://twitter.com/theRcast) (X/Twitter) Mike Thomas: @mike_thomas@fosstodon.org (https://fosstodon.org/@mike_thomas) (Mastodon) and @mike_ketchbrook (https://twitter.com/mike_ketchbrook) (X/Twitter) Music credits powered by OCRemix (https://ocremix.org/) Kannonball - Donkey Kong Country 2: Diddy Kong's Quest - The Good Ice - https://ocremix.org/remix/OCR04571 The Art of Zoning Out - Pokemon Scarlet - timaeus222 - https://ocremix.org/remix/OCR04570

Redan efter 26 avsnitt bjuder Studio Ladan in till livepodd på O'Learys i Umeå. Fantastiska gäster, god mat och trevligt sällskap utlovas. Bordsbokning och mer information hittar ni på vk.se/livepodd.

Brian Underdahl, a multifaceted expert in multifamily real estate and macroeconomic research, holds an MS in Applied Economics from FSU. As CEO at QRE Partners, he led key roles in acquiring and managing U.S. apartment buildings, aligning investments with market trends. Brian's data-centric approach, using tools like Rstudio and Python, has shaped transparent and evidence-based strategies. His influence extends beyond real estate, contributing significantly to industry thought leadership through data analysis and macroeconomic research.   Here's some of the topics we covered:   Brian's Background From Sales To Economics An Alternative Option For Sellers $136B In Commercial Debt Coming Due This Year Caution About Rate Cuts During 2024 Will The Fed Print More Money? Hyper Inflation and Money Becoming Worthless Savings & Loan Crisis China's Reluctance to Rely on the US Dollar Opportunity In Other Sectors Of The Economy   To find out more about partnering or investing in a multifamily deal: Text Partner to 72345 or email Partner@RodKhleif.com    For more about Rod and his real estate investing journey go to www.rodkhleif.com   Please Review and Subscribe  

How the {potools} package jump-starts your R package translations, the most-upvoted feature request lands in the RStudio IDE with GitHub Copilot integration, and a reflective post on the multiple paths to reproducible data science workflows in R. Episode Links This week's curator: Jon Calder (@jonmcalder (https://twitter.com/jonmcalder)) (Twitter) How to translate your package's messages with {potools} (https://masalmon.eu/2023/10/06/potools-mwe/) GitHub Copilot in Rstudio, it's finally here! (https://www.youtube.com/watch?v=yVq-b5xHmac) An overview of what's out there for reproducibility with R (https://www.brodrigues.co/blog/2023-10-05-repro_overview/) Entire issue available at rweekly.org/2023-W41 (https://rweekly.org/2023-W41.html) Supplement Resources potools - Tools for Portability and Internationalization of R packages https://michaelchirico.github.io/potools/ GitHub Copilot in RStudio, it's finally here! https://colorado.posit.co/rsc/rstudio-copilot/ GitHub Copilot RStudio User Guide: https://docs.posit.co/ide/user/ide/guide/tools/copilot.html Rami Krispin's GitHub repo on devcontainers w/ R in VSCode: https://github.com/RamiKrispin/vscode-r R/Pharma virtual conference registration: https://hopin.com/events/r-pharma-2023/registration R/Pharma 2023 workshops (please register for conference before your register for a workshop): https://rinpharma.com/workshop/2023conference/ Supporting the show Use the contact page at https://rweekly.fireside.fm/contact to send us your feedback R-Weekly Highlights on the Podcastindex.org (https://podcastindex.org/podcast/1062040) - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby (https://getalby.com/), and then head over to the R-Weekly Highlights podcast entry on the index. A new way to think about value: https://value4value.info Get in touch with us on social media Eric Nantz: @theRcast (https://twitter.com/theRcast) (Twitter) and @rpodcast@podcastindex.social (https://podcastindex.social/@rpodcast) (Mastodon) Mike Thomas: @mike_ketchbrook (https://twitter.com/mike_ketchbrook) (Twitter) and @mike_thomas@fosstodon.org (https://fosstodon.org/@mike_thomas) (Mastodon) Music credits powered by OCRemix (https://ocremix.org/) Person, Place, or Groove? - Pictionary - The Orichalcon - https://ocremix.org/remix/OCR01548 Forest Through the Trees - Final Fantasy Mystic Quest - Shea's Violin - https://ocremix.org/remix/OCR04484

In this episode, we're joined by JJ Allaire, Founder and CEO of Posit, the maker of open source software for data science and scientific research, best known for their multi-language development environment, RStudio. During the conversation, JJ shares detail on his personal journey as an entrepreneur and software developer, the evolution of Posit, and its role as a Public Benefit Corporation. He discusses his views on machine learning, the limitations of large language models, and the importance of contributing to the open source community. Hosted on Acast. See acast.com/privacy for more information.

Today I had the pleasure of interviewing JJ Allaire. J.J. is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown publishing ecosystem including rmarkdown, flexdashboard, learnr, and distill, and also worked extensively on the R interfaces to Python, Spark, and TensorFlow. J.J. is now leading the Quarto project, which is a new Jupyter-based scientific and technical publishing system. In this episode we learn about why RStudio has now repositioned itself as posit, how it maximizes its open source nature as a B corp, and how JJ as a open source advocate views the private nature of many LLMs. I really enjoyed this conversation, and I hope you will as well! Posit - https://posit.co/Podcast Sponsors, Affiliates, and Partners:- Pathrise - http://pathrise.com/KenJee | Career mentorship for job applicants (Free till you land a job)- Taro - http://jointaro.com/r/kenj308 (20% discount) | Career mentorship if you already have a job - 365 Data Science (57% discount) - https://365datascience.pxf.io/P0jbBY | Learn data science today- Interview Query (10% discount) - https://www.interviewquery.com/?ref=kenjee |  Interview prep questions

Releasing an Word document table into the land of markdown, a practical overview of sharing your machine learning model with others, and taking local control of checking the builds of your package across computing architectures. Episode Links This week's curator: Colin Fay - [@ColinFay]](https://twitter.com/ColinFay) (Twitter) Convert a Word table to Markdown (https://www.rostrum.blog/2023/06/21/wordup-tables/) How Can Someone Else Use My Model? (https://matthewrkaye.com/posts/series/doing-data-science/2023-06-20-how-can-others-use-my-model/how-can-others-use-my-model.html) How to debug your package in a {rhub} fedora container before sending to CRAN? (https://statnmap.com/2023-06-20-how-to-debug-your-package-in-a-rhub-fedora-container-before-sending-to-cran/) Entire issue available at rweekly.org/2023-W26 (https://rweekly.org/2023-W26.html) Supplement Resources {datapasta} RStudio addins and R functions that make copy-pasting vectors and tables to text painless https://milesmcbain.github.io/datapasta Matt Kaye's series "The missing semester of your DS education" https://matthewrkaye.com/series.html#the-missing-semester-of-your-ds-education Put R in production: Tools and guides to put R models in production https://putrinprod.com {checkhelper} A package to help you deal with devtools::check outputs https://thinkr-open.github.io/checkhelper Remote Explorer Visual Studio Code extension https://marketplace.visualstudio.com/items?itemName=ms-vscode.remote-explorer {crew}: A distributed worker launcher framework for asynchronous and distributed computing https://wlandau.github.io/crew Data4Good Explores Visualizing Freshwater Resources on a Global Scale https://appsilon.com/visualizing-fresh-water-resources-data Supporting the show Use the contact page at https://rweekly.fireside.fm/contact to send us your feedback R-Weekly Highlights on the Podcastindex.org (https://podcastindex.org/podcast/1062040) - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby (https://getalby.com/), and then head over to the R-Weekly Highlights podcast entry on the index. A new way to think about value: https://value4value.info Get in touch with us on social media Eric Nantz: @theRcast (https://twitter.com/theRcast) (Twitter) and @rpodcast@podcastindex.social (https://podcastindex.social/@rpodcast) (Mastodon) Mike Thomas: @mike_ketchbrook (https://twitter.com/mike_ketchbrook) (Twitter) and @mike_thomas@fosstodon.org (https://fosstodon.org/@mike_thomas) (Mastodon)

In this episode of Future-Proof Your Career, we speak to Caroline Keep, a data scientist, a teacher, a maker, and a researcher in machine learning. She is the recipient of multiple awards, including the Times Education Supplement teacher award, and a founder of Liverpool Makerfest. We spoke to Caroline about how you extract meaning from data, and how we can all be more engaged in the effort to decipher the world around us. Here's what we learned. Data is the real world, quantified Don't think of data as just endless spreadsheets and numbers. It's a representation of the real world and the things that matter. Understanding the data is a way to understand the world. Understanding data is a process Caroline talked about multiple steps in the ‘data cycle': Start with discovery: play with the data at your disposal to get a feel for itCreate a hypothesis: what are you trying to test?Discuss your idea with other people and gather perspectives, check your reasoningClean your data: the real world is messy and full of bias and noiseTest your idea: does your hypothesis hold true? Build domain knowledge  Understanding the space you're exploring is critical to give you a reference point. Otherwise you won't know if the results you find are nonsense! If the data you want doesn't exist, you can get it There are lots of sources of interesting data, but the Internet of Things makes it cheaper and easier than ever to collect data that doesn't exist. Whether you want to track temperature, movement, light or pollution, or anything for that matter, simple sensors and cheap computers like the Raspberry Pi allow anyone to experiment (see links below) Caroline referenced some great resources and projects, including: Kaggle: a data science community - https://www.kaggle.com/NodeRed: a drag and drop IoT platform: https://nodered.org/Kettle Companion: A connected kettle that helps carers keep an eye on vulnerable people - https://kettlecompanion.com/Rstudio: software for data science - https://posit.co/products/open-source/rstudio/Python: a powerful but accessible programming language - https://www.python.org/Jupyter Notebook: https://jupyter.org/

Introducing the new ggflowchart package, how a dockerized development environment is another win for reproducibility, and our take on Colin Fay's keynote from the Appsilon Shiny Conference. Episode Links This week's curator: Sam Parmar - @parmsam_ (https://twitter.com/parmsam_) (Twitter) & @parmsam@fosstodon.org (https://fosstodon.org/@parmsam) (Mastodon) Introducing {ggflowchart} (https://nrennie.rbind.io/blog/introducing-ggflowchart/) Why you should consider working on a dockerized development environment (https://www.brodrigues.co/blog/2023-05-08-dock_dev_env/) Colin Fay, Keynote: Production is like ultra running: brutal, ungrateful, but worth every step (https://www.youtube.com/watch?v=wMbhxTJNrmw) Entire issue available at rweekly.org/2023-W20 (https://rweekly.org/2023-W20.html) Supplement Resources Episode 82 (the origins of ggflowchart) https://rweekly.fireside.fm/82 Building reproducible analytical pipelines with R https://raps-with-r.dev The Rocker Project https://rocker-project.org Shiny Dev Series Livestream: Fully containerized R dev environment with Docker, RStudio, and VS-Code https://www.youtube.com/watch?v=4wRiPG9LM3o Development Container Features https://code.visualstudio.com/blogs/2022/09/15/dev-container-features r2u: CRAN as Ubuntu binaries https://eddelbuettel.github.io/r2u/ A preview of Eric and Mike's Production Shiny Workshop https://www.youtube.com/watch?v=MlRwhDYI5Ec Supporting the show Use the contact page at https://rweekly.fireside.fm/contact to send us your feedback Get a New Podcast App and send us a boost! https://podcastindex.org/apps?elements=Boostagrams%2CValue Support creators with boostagrams using Podverse and Alby: https://blog.podverse.fm/support-creators-with-boostagrams-and-streaming-sats-using-podverse-and-alby/ A new way to think about value: https://value4value.info Get in touch with us on social media Eric Nantz: @theRcast (https://twitter.com/theRcast) (Twitter) and @rpodcast@podcastindex.social (https://podcastindex.social/@rpodcast) (Mastodon) Mike Thomas: @mike_ketchbrook (https://twitter.com/mike_ketchbrook) (Twitter) and @mike_thomas@fosstodon.org (https://fosstodon.org/@mike_thomas) (Mastodon)

Our first episode of 2023 covers the brand-new gpttools package to called chatGPT directly in R, a wholistic look at MLOps with the latest tidymodels tooling, and a spotlight on the lesser-known quantile regression. Plus listener feedback and much more! Episode Links This week's curator: Kelly Bodwin (@KellyBodwin (https://twitter.com/KellyBodwin)) {gpttools} for Chat GPT in RStudio (https://jameshwade.github.io/gpttools/) MLOps: The Whole Game (https://jameshwade.com/posts/2022-12-27_mlops-the-whole-game.html) Quantile Regression (https://yuzar-blog.netlify.app/posts/2022-12-01-quantileregression/) Entire issue available at rweekly.org/2022-W52 (https://rweekly.org/2022-W52.html) Supplement Resources Why Everyone's Obsessed With ChatGPT, a Mind-Blowing AI Chatbot https://www.cnet.com/tech/computing/why-everyones-obsessed-with-chatgpt-a-mind-blowing-ai-chatbot Yury's quantile regression video: https://www.youtube.com/watch?v=Gtz8ca_4hVg What is R7? A New OOP System for R https://www.jumpingrivers.com/blog/r7-oop-object-oriented-programming-r R Weekly Highlights Episode 98 https://podverse.fm/episode/VvyuAA4kj Shiny Dev Series episodes with Mike discussing the Connective COVID-19 Test Spotter App: Part 1: https://shinydevseries.com/interview/ep030 Part 2: https://shinydevseries.com/interview/ep031 Supporting the show Use the contact page at https://rweekly.fireside.fm/contact to send us your feedback Get a New Podcast App and send us a boost! https://podcastindex.org/apps?appTypes=app&elements=Value A new way to think about value: https://value4value.info Get in touch with us on social media: Eric: @theRcast (https://twitter.com/theRcast) (Twitter) and @rpodcast@podcastindex.social (https://podcastindex.social/@rpodcast) (Mastodon) Mike: @mike_ketchbrook (https://twitter.com/mike_ketchbrook) (Twitter) and @mike_thomas@fosstodon.org (https://fosstodon.org/@mike_thomas) (Mastodon)

Summary Building a machine learning model one time can be done in an ad-hoc manner, but if you ever want to update it and serve it in production you need a way of repeating a complex sequence of operations. Dagster is an orchestration engine that understands the data that it is manipulating so that you can move beyond coarse task-based representations of your dependencies. In this episode Sandy Ryza explains how his background in machine learning has informed his work on the Dagster project and the foundational principles that it is built on to allow for collaboration across data engineering and machine learning concerns. Interview Introduction How did you get involved in machine learning? Can you start by sharing a definition of "orchestration" in the context of machine learning projects? What is your assessment of the state of the orchestration ecosystem as it pertains to ML? modeling cycles and managing experiment iterations in the execution graph how to balance flexibility with repeatability What are the most interesting, innovative, or unexpected ways that you have seen orchestration implemented/applied for machine learning? What are the most interesting, unexpected, or challenging lessons that you have learned while working on orchestration of ML workflows? When is Dagster the wrong choice? What do you have planned for the future of ML support in Dagster? Contact Info LinkedIn (https://www.linkedin.com/in/sandyryza/) @s_ryz (https://twitter.com/s_ryz) on Twitter sryza (https://github.com/sryza) on GitHub Parting Question From your perspective, what is the biggest barrier to adoption of machine learning today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast (https://www.dataengineeringpodcast.com) covers the latest on modern data management. Podcast.__init__ () covers the Python language, its community, and the innovative ways it is being used. Visit the site (https://www.themachinelearningpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@themachinelearningpodcast.com (mailto:hosts@themachinelearningpodcast.com)) with your story. To help other people find the show please leave a review on iTunes (https://podcasts.apple.com/us/podcast/the-machine-learning-podcast/id1626358243) and tell your friends and co-workers Links Dagster (https://dagster.io/) Data Engineering Podcast Episode (https://www.dataengineeringpodcast.com/dagster-software-defined-assets-data-orchestration-episode-309/) Cloudera (https://www.cloudera.com/) Hadoop (https://hadoop.apache.org/) Apache Spark (https://spark.apache.org/) Peter Norvig (https://en.wikipedia.org/wiki/Peter_Norvig) Josh Wills (https://www.linkedin.com/in/josh-wills-13882b/) REPL == Read Eval Print Loop (https://en.wikipedia.org/wiki/Read%E2%80%93eval%E2%80%93print_loop) RStudio (https://posit.co/) Memoization (https://en.wikipedia.org/wiki/Memoization) MLFlow (https://mlflow.org/) Kedro (https://kedro.readthedocs.io/en/stable/) Data Engineering Podcast Episode (https://www.dataengineeringpodcast.com/kedro-data-pipeline-episode-100/) Metaflow (https://metaflow.org/) Podcast.__init__ Episode (https://www.pythonpodcast.com/metaflow-machine-learning-operations-episode-274/) Kubeflow (https://www.kubeflow.org/) dbt (https://www.getdbt.com/) Data Engineering Podcast Episode (https://www.dataengineeringpodcast.com/dbt-data-analytics-episode-81/) Airbyte (https://airbyte.com/) Data Engineering Podcast Episode (https://www.dataengineeringpodcast.com/airbyte-open-source-data-integration-episode-173/) The intro and outro music is from Hitman's Lovesong feat. Paola Graziano (https://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Tales_Of_A_Dead_Fish/Hitmans_Lovesong/) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/)/CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0/)

Max Kuhn is a software engineer at RStudio. He is currently working on improving R's modeling capabilities and maintains about 30 packages, including caret. He was a Senior Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was... The post Episode #227: Max Kuhn appeared first on PolicyViz.

Max Kuhn is a software engineer at RStudio. He is currently working on improving R's modeling capabilities and maintains about 30 packages, including caret. He was a Senior Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years. Max has a Ph.D. in Biostatistics. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015. Their second book, Feature Engineering and Selection, was published in 2019 and his book with Julia Silge, Tidy Models with R, was published in 2022. Episode Notes Website at RStudio: https://www.rstudio.com/authors/max-kuhn/Twitter: https://twitter.com/topeposGithub: https://github.com/topepo R Packages:autoMLcaretQuartoRMarkdowntidymodelstidyverse Books from Max:Tidy Modeling with R: A Framework for Modeling in the TidyverseApplied Predictive ModelingFeature Engineering and Selection R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Garrett Grolemund and Hadley Wickham Related Episodes Episode #225: Julia SilgeEpisode #212: Dr. Cedric SchererEpisode #210: Dr. Tyler Morgan-WallEpisode #207: Tom MockEpisode #150: Learning REpisode #69: Hadley Wickham iTunes

On this episode of the Sand Podcast we have Camera Man Chris of I.N.R Studio chilling with us. We talk briefly about how Chris got into making videos and his podcast, Team Rico, off the record. Money also tells a story about his first days getting into trucking. You find Team Rico in the link below https://youtube.com/channel/UCC1uBCyepbo61nYVA79Quug

In the past, Introduction to Statistics classes spent a lot of time covering distribution tables, teaching students to run stats by hand and focusing on statistical procedures. However, educators are continually considering new ways to teach stats, and the increasing popularity of data science makes it a more urgent prospect for some. That's the focus of this episode of Stats and Stories with guest Mine Çetinkaya-Rundel. Mine Çetinkaya-Rundel (@minebocek) is a senior lecturer at University of Edinburgh, an associate professor of the practice at Duke University, and a professional educator at RStudio. She has author of three open source statistics textbooks and is an instructor for Coursera. Her work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education. She works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. In addition to her academic position, she also works with RStudio, where her focus is primarily on education for open-source R packages as well as building resources and tools for educators teaching statistics and data science with R and RStudio. How did stats pedagogy become a focus for you? 1:00 Changes in statistics education 2:36  How has the public nature of data and statistical data affected you? 7:13 How do you get students to think about ethics when they're grabbing data? 9:28 Current practitioners 12:43  People that take one stats class 17:17 The future of this practice. 23:41

Avoid repeating yourself by using dplyr's across function, going inside the process of creating a custom theme in ggplot2, and a few keyboard-centric tricks to manage your RStudio pane viewing. Episode Links This week's curator: Ryo Nakagawara (@RbyRyo (https://twitter.com/R_by_Ryo)) Using across() to create multiple columns (https://www.njtierney.com/post/2022/08/08/fun-across/) Pretty ggplots with custom themes, ggtext, and ggh4x (https://www.michaelc-m.com/ggplot-extensions-and-custom-themes/) Window and Pane Management Tricks for RStudio and your OS (https://datachimp.app/blog/window-managment-for-rstudio/) Entire issue available at rweekly.org/2022-W33 (https://rweekly.org/2022-W33.html) Supplement Resources {ggh4x}: https://teunbrand.github.io/ggh4x/index.html

We're officially one month into NHL free agency. Not only that, but Josh wrote a review for the site covering the last month! We chat about the contents of said review, general salary trends, annoying contracts, month rankings (yes), and RStudio themes. Check out the article here: https://evolving-hockey.com/blog/2022-nhl-free-agency-a-review/

RStudio re-brands as Posit, the shinytest2 package continues to make waves in the Shiny community, and more Quarto tips to boost your workflow. Episode Links This week's curator: Kelly Bodwin (@KellyBodwin (https://twitter.com/KellyBodwin)) RStudio rebrands as Posit (https://www.rstudio.com/blog/rstudio-is-becoming-posit/) {shinytest2}: For testing Shiny apps. (https://rstudio.github.io/shinytest2/) (slides (http://schloerke.com/presentation-2022-07-28-rstudioconf22-shinytest2/)) One Quarto tip a day (https://mine-cetinkaya-rundel.github.io/quarto-tip-a-day/) Entire issue available at rweekly.org/2022-W31 (https://rweekly.org/2022-W31.html) Supplement Resources JJ Allaire and Jeremy Howard 2-way AMA: https://www.youtube.com/watch?v=xxVVSxcjNQs Tom Mock's Welcome to Quarto online event (August 9, 2023): https://www.addevent.com/event/Eh13574863

Another great use case for Docker containers with interactive R-Markdown reports, a recap of RStudio's presence at the Appsilon Shiny conference, and building an interactive point-and-click game with Shiny. Episode Links This week's curator: Jonathan Carroll (@carroll_jono (https://twitter.com/carroll_jono)) Containerizing Interactive R Markdown Documents (https://hosting.analythium.io/containerizing-interactive-r-markdown-documents/) RStudio Recap From the Appsilon Shiny Conference (https://www.rstudio.com/blog/rstudio-recap-from-the-appsilon-shiny-conference/) How to build an interactive point-and-click game with {Shiny} (https://www.youtube.com/watch?v=4-6jDDCADvU) Entire issue available at rweekly.org/2022-W28 (https://rweekly.org/2022-W28.html) Supplement Resources Appsilon Shiny Conference playlist: https://www.youtube.com/playlist?list=PLexAKolMzPcrYjGA1PULfm7-P12qjKmPb R Workflow by Frank Harrell: http://hbiostat.org/rflow/ Albert's video on styling a Quarto blog with CSS: https://www.youtube.com/watch?v=ErRX8plZpQE

Show Notes(01:35) Ville recalled his education getting degrees in Computer Science from the University of Helsinki in Finland.(04:35) Ville walked over his time working at a startup called Gurusoft that planned to commercialize self-organizing maps, a peculiar artificial neural network.(07:17) Ville reflected on his four years as a researcher at Nokia — working on big data infrastructure, analytics, and ML open-source projects (such as Disco and Ringo).(11:56) Ville shared the story of co-founding a startup that built a novel scriptable data platform called Bitdeli with his brother and not finding a product-market fit.(13:58) Ville walked through AdRoll's acquisition of Bitdeli in June 2013.(15:49) Ville discussed the engineering challenges associated with his work at AdRoll — AdRoll Prospecting and traildb.io.(19:33) Ville mentioned the product and leadership/management lessons during his time being AdRoll's Head of Data and leading various data/ML efforts.(24:43) Ville rationalized his decision to join the ML Infrastructure team at Netflix in 2017.(27:26) Ville discussed the motivation behind the creation of Netflix's human-centric ML infrastructure, Metaflow, later open-sourced in 2019.(30:21) Ville unpacked the key design principles that summarize the philosophy of Metaflow, which is influenced by the unique culture at Netflix.(35:00) Ville talked about his well-known diagram on the data infrastructure's hierarchy of needs.(37:33) Ville examined the technical details behind Metaflow's integration with AWS to make it easy for users to move back and forth between their local and remote modes of development and execution.(40:58) Ville expressed the challenges of finding Metaflow's early adopters internally at Netflix and externally later on at other companies.(45:13) Ville went over the strategy around prioritizing features for Metaflow's future roadmap.(52:22) Ville shared the story behind the founding of Outerbounds, which he co-founded with Savin Goyal and Oleg Avdeev.(55:03) Ville provided his thoughts behind Metaflow's contributors in a way that can generate valuable product feedback for Outerbounds.(58:30) Ville shared valuable hiring lessons to attract the right people who are excited about Outerbounds' mission.(01:01:28) Ville shared upcoming initiatives that he is most excited about for Outerbounds.(01:04:05) Ville walked through his writing process for an upcoming technical book with Manning called “Effective Data Science Infrastructure,” a hands-on guide to assembling infrastructure for data science and machine learning applications.(01:06:34) Ville unpacked his great O'Reilly article that digs deep into the fundamentals of ML as an engineering discipline.(01:11:03) Closing segment.Ville's Contact InfoLinkedInTwitterGitHubOuterboundsWebsite | Twitter | LinkedIn | GitHub | YouTubeMetaflow GitHub | Metaflow DocsSlack CommunityCareersMetaflow Resources for Data ScienceMetaflow Resources for EngineeringMentioned ContentTalksSF Data Mining Meetup: TrailDB — Processing Trillions of Events at AdRoll (July 2016)QConSF 2018: Human-Centric Machine Learning Infrastructure @Netflix (Feb 2019)AWS re:Invent 2019: More Data Science with Less Engineering — ML Infrastructure at Netflix (Dec 2019)Scale By The Bay 2019: Human-Centric ML Infrastructure at Netflix (Jan 2020)AICamp: Metaflow — The ML Infrastructure at Netflix (Aug 2021)ArticlesOpen-Sourcing Metaflow, a Human-Centric Framework for Data Science (Netflix Tech Blog, Dec 2019)Unbundling Data Science Workflows with Metaflow and AWS Step Functions (Netflix Tech Blog, July 2020)MLOps and DevOps: Why Data Makes It Different (O'Reilly, Oct 2021)PeopleMichael Jordan (Distinguished Professor in EECS and Statistics at UC Berkeley)Matthew Honnibal and Ines Montani (Creators of open-source NLP library spaCy)Hadley Wickham (Chief Scientist at RStudio and Adjunct Professor of Statistics at Rice University)Book“The Mom Test” (by Rob Fitzpatrick)NotesMy conversation with Ville was recorded back in October 2021. Since then, many things have happened at Outerbounds. I'd recommend:Visiting Outerbounds' new website with Metaflow resources for Data Science and EngineeringWatching Ville's recent talk at Data Council Austin about the Modern Stack for ML InfrastructureBuying Ville's newly released book “Effective Data Science Infrastructure”About the showDatacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com.Subscribe by searching for Datacast wherever you get podcasts or click one of the links below:Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you're new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Earlier this year at RStudio Global, a lot of excitement among the Shiny enthusiasts centered on the brand new bslib and thematic packages for radically changing the style of typical Shiny app user interfaces. I am thrilled to get the inside story on this amazing development with the brilliant author, RStudio software engineer Carson Sievert! In this episode you will hear Carson's recommendations on getting started with bslib for both Shiny applications and even R-Markdown documents, why SASS (no, not that one) rules empower a Shiny developer to make sweeping changes in CSS, as well as the major milestone release of shinymeta, a package that directly addresses a huge need for traceable and reproducible analyses from Shiny apps in many industries such as life sciences. I hope you enjoy this episode and don't forget to subscribe to our channel so you can be first to know when future episodes are available!Resources mentioned in the episodeInteractive web-based data visualization with R, plotly, and shinybslib: Tools for theming shiny and rmarkdown from R via Bootstrap (3 or 4) Sass rstudio.github.io/bslibthematic: Simplified theming of ggplot2, lattice, and base R graphics rstudio.github.io/thematicshinymeta: Record and expose Shiny app logic using metaprogramming rstudio.github.io/shinymetaflexdashboard: Easy interactive dashboards for R pkgs.rstudio.com/flexdashboardEpisode Timestamps00:00:00 Episode Introduction 00:02:00 Joining the Shiny team at RStudio and Carson's book on plotly 00:06:39 Introducing bslib and how it makes custom theming of your Shiny app as easy as possible 00:08:47 Introducing thematic for simplified theming of ggplot2, lattice, and base R graphics 00:14:28 Getting started with bslib 00:23:45 Real-time theming wizard, a tool to play interactively with the theming customization of your shiny app or R Markdown document 00:29:25 Development version of flexdashboard supports bslib now 00:36:38 On the advantages of working with sass over css. bslib helps you work with a front end web developer, writing sass rules and css styles while not having to dive into your Shiny app or R Markdown document 00:46:30 The origins of shinymeta and the ability to fully extract an app's reactive processing to produce a fully self-contained analysis script or report 00:57:40 Getting started with shinymeta 01:01:20 Shinymeta example of producing reproducible Shiny code 01:05:36 How does Carson recommend to Shiny developers who want to get better at cusotmizing the look and feel of their Shiny app? See Shiny's Build articles 01:15:35 Attaching metadata to graphical markers in plotly 01:19:47 Episode wrapup

Earlier this year at RStudio Global, a lot of excitement among the Shiny enthusiasts centered on the brand new bslib and thematic packages for radically changing the style of typical Shiny app user interfaces. I am thrilled to get the inside story on this amazing development with the brilliant author, RStudio software engineer Carson Sievert! In this episode you will hear Carson's recommendations on getting started with bslib for both Shiny applications and even R-Markdown documents, why SASS (no, not that one) rules empower a Shiny developer to make sweeping changes in CSS, as well as the major milestone release of shinymeta, a package that directly addresses a huge need for traceable and reproducible analyses from Shiny apps in many industries such as life sciences. I hope you enjoy this episode and don't forget to subscribe to our channel so you can be first to know when future episodes are available! Resources mentioned in the episode Interactive web-based data visualization with R, plotly, and shiny (https://plotly-r.com) bslib: Tools for theming shiny and rmarkdown from R via Bootstrap (3 or 4) Sass rstudio.github.io/bslib (https://rstudio.github.io/bslib) thematic: Simplified theming of ggplot2, lattice, and base R graphics rstudio.github.io/thematic (https://rstudio.github.io/thematic) shinymeta: Record and expose Shiny app logic using metaprogramming rstudio.github.io/shinymeta (https://rstudio.github.io/shinymeta) flexdashboard: Easy interactive dashboards for R pkgs.rstudio.com/flexdashboard (https://pkgs.rstudio.com/flexdashboard) Episode Timestamps 00:00:00 (https://youtube.com/watch?v=xTafvYX3zmE&t=0s) Episode Introduction 00:02:00 (https://youtube.com/watch?v=xTafvYX3zmE&t=120s) Joining the Shiny team at RStudio and Carson's book on plotly 00:06:39 (https://youtube.com/watch?v=xTafvYX3zmE&t=399s) Introducing bslib and how it makes custom theming of your Shiny app as easy as possible 00:08:47 (https://youtube.com/watch?v=xTafvYX3zmE&t=527s) Introducing thematic for simplified theming of ggplot2, lattice, and base R graphics 00:14:28 (https://youtube.com/watch?v=xTafvYX3zmE&t=868s) Getting started with bslib 00:23:45 (https://youtube.com/watch?v=xTafvYX3zmE&t=1425s) Real-time theming wizard, a tool to play interactively with the theming customization of your shiny app or R Markdown document 00:29:25 (https://youtube.com/watch?v=xTafvYX3zmE&t=1765s) Development version of flexdashboard supports bslib now 00:36:38 (https://youtube.com/watch?v=xTafvYX3zmE&t=2198s) On the advantages of working with sass over css. bslib helps you work with a front end web developer, writing sass rules and css styles while not having to dive into your Shiny app or R Markdown document 00:46:30 (https://youtube.com/watch?v=xTafvYX3zmE&t=2790s) The origins of shinymeta and the ability to fully extract an app's reactive processing to produce a fully self-contained analysis script or report 00:57:40 (https://youtube.com/watch?v=xTafvYX3zmE&t=3460s) Getting started with shinymeta 01:01:20 (https://youtube.com/watch?v=xTafvYX3zmE&t=3680s) Shinymeta example of producing reproducible Shiny code 01:05:36 (https://youtube.com/watch?v=xTafvYX3zmE&t=3936s) How does Carson recommend to Shiny developers who want to get better at cusotmizing the look and feel of their Shiny app? See Shiny's Build articles 01:15:35 (https://youtube.com/watch?v=xTafvYX3zmE&t=4535s) Attaching metadata to graphical markers in plotly 01:19:47 (https://youtube.com/watch?v=xTafvYX3zmE&t=4787s) Episode wrapup

Det finns både utrikespolitiska och inrikespolitiska skäl till att Turkiet motsätter sig Sveriges medlemskap i Nato. President Erdogan använder sin vetorätt för att vinna så stora fördelar som möjligt. Kraven riktar sig mot Sverige, som han har oplockade gäss med, men det han verkligen vill ha kan framför allt levereras av USA. Konfrontationen tjänar också till att visa upp presidenten som kraftfull ledare i ett läge där det ser ytterst besvärligt ut på hemmaplan vad gäller både ekonomi och politik. Det säger Thomas Gür, företagare, skribent och Turkietkännare. Han samtalar med programledaren PJ Anders Linder.

Foundations of Amateur Radio The amateur radio community is as varied as humanity across the globe. It represents an endless supply of ideas and experiments that continue to attract people looking for something new and exiting. On the face of it, our hobby is about radio and electronics, about propagation and antennas, about modes and contacts, but if you limit your outlook to those topics you'll miss out on a vast expanse of opportunity that is only just beginning to emerge. Until quite recently, computing in amateur radio was essentially limited to logging and contest scoring. It has evolved to include digital modes like PSK31 and the advent of smaller, faster and cheaper computers in the home has brought the possibility of processing unimaginable amounts of data leading to modes like WSPR and FT8. In the past I've spoken about how amateur radio means different things to different people. Making contact using a digital internet enabled repeater is sacrileges to one and manna from heaven to another. Between those two extremes there is room to move and explore. Similarly where one uses valves, another expects an integrated circuit. One wants low power, the other wants every Watt they can lay their hands on. Contesting versus rag chewing, nets vs contacts, SSB vs. CW, FT8 vs. RTTY. Each of these attracts a different part of the community with different outcomes and expectations. For some it's about antenna building, others going portable, climbing a mountain, or setting up in a park. Those are all traditional amateur activities, but the choice and opportunity don't end there. The longer I play with computers the more I see a convergence in the world, a coming together of technologies and techniques. I've talked about some of this before when in 1994 I produced a competition broadcast promotion for the radio station I was working at, using just a computer in the era of reel-to-reel tape and razor blades. My station manager couldn't quite put his finger on what was different, but with hindsight it represented a landslide change in how radio stations have operated since. Mind you, I'm not saying that I was the first, just the first in that particular radio station. In many ways computing is an abstract effort. When asked, I like to express it as designing something intangible in an imaginary world using an made up language and getting paid real money to make it happen, well, numbers in my bank account at least. Within that context, amateur radio is slowly beginning to reap the rewards that come from the exponential growth in home computing power. While the majority of humanity might use the vast amount of CPU cycles to scroll through cat videos online, that access to processing power allows us to do other things as well. For example, right now I'm playing with the dataset that represents all the WSPR spots since March of 2008. As of now there are around four billion rows of contacts, containing data points like a time-stamp, the transmitter, the receiver, the signal strength, location, direction, and more. As part of that investigation I went looking for documents containing the words "RStudio" and "maidenhead", so I could consider creating a map in my statistical tool that allowed me to represent my dataset. In making that search I discovered a thesis by a mathematician who was using the reverse beacon network in an attempt to predict which station could hear which transmitter at what time. In reading the thesis, which I opened because I was looking for an example on how to convert a maidenhead locator into geo-spacial data types in R, a popular statistics platform, I discovered that the author didn't appear to have much, if any, amateur knowledge or experience, but they approached their task, attempting to predict as a mathematician what we in our community call propagation, based on a public dataset, downloaded straight from the reverse beacon network, created by amateurs like you and I. This interaction between science and the amateur community isn't new. Sometimes it's driven by science, other times it's driven by amateur radio. There's a team exploring the ionospheric prediction models that we've used for decades, popularly referred to as VOACAP or Voice of America Coverage Analysis Program, based on multiple evolutions of empirical models of the ionosphere that were first developed in the 1960's, headed by both a scientist and an amateur, Chris KL3WX. With the advent of WSPR and the associated data collection some experiments have started to compare the reality of propagation as logged by WSPR to the predicted propagation as modelled by VOACAP. One such experiment happened in 2018 where Chris and his team at HAARP, the High-Frequency Active Auroral Research Program, set out to make transmissions at specific times and frequencies, using the amateur community logging of WSPR spots to compare their transmissions to the predictions. Interestingly they did not match. Just think about that for a moment. The tool we love and use all across our community, VOACAP, doesn't match the reality of propagation. My own playing with WSPR data is driven by the very same thing that I use to be a better contester, a burning curiosity in all things. My VOACAP prediction experience has been poor to date. Setting up my own WSPR beacon is the first step in attempting to discover what my actual propagation looks like, but in doing so, it's also a possible contribution to the wider challenges of predicting propagation based on a dataset with four billion spots. One such approach might be to create an ionospheric prediction map based on actual data and compare that to the models as well as the published space weather maps and combining these efforts into a machine learning project which might give us the next generation of ionospheric prediction tools, but only time will tell. No doubt I will have to learn more about statistics and machine learning than I expect, but then, that's half the fun. So, next time you think of amateur radio as being limited to valves, transistors, soldering, antennas and rag chewing on HF, consider that there might be other aspects to this hobby that you have not yet considered. What other research are you aware of that relates to amateur radio? I'm Onno VK6FLAB

Hilary and Roger discuss whether they understand their models, changing programming languages, using RStudio for everything, and deep learning.   Show Notes: Support us on Patreon Roger on Twitter Hilary on Twitter List of NSSD Fellows Get the Not So Standard Deviations book Subscribe to the podcast on Apple Podcasts Subscribe to the podcast on Google Play Find past episodes Contact us at nssdeviations @ gmail.com Podcast art by Jessica Crowell

What is the Tidyverse and why is it important? Hadley Wickham is a leading data scientist and advocate for improving data science with tidy data and data hygiene. He's the Chief Scientist at RStudio and an Adjunct Professor of Statistics at the University of Oakland, Stanford University and Rice University. Join the Tidyverse discussion with The Data Wranglers Joe Hellerstein and Jeffrey Heer. #TheDataWranglers

Tom works at RStudio, and is obviously very active in the R community. He runs the TidyTuesday project and developed the Grammar of Tables package in the R programming language. The post Episode #207: Tom Mock appeared first on PolicyViz.

A major announcement for R developers interested in type safety, thoughts on using Visual Studio Code from the perspective of a long-time RStudio user, and the adventures of filling regions between lines with ggplot2. Episode Links This week's curator: Ryo Nakagawara (@RbyRyo (https://twitter.com/R_by_Ryo)) Introducing rpp: The long-term goal of the organisation is to add static type checking and other features to R, with zero cost at run time (https://blog.q-lang.org/posts/2021-10-13-release/) How not to be lost with VSCode when coming from RStudio? (https://statnmap.com/2021-10-09-how-not-to-be-lost-with-vscode-when-coming-from-rstudio/) Fill the region between two lines in ggplot2 (https://www.nsgrantham.com/fill-between-two-lines-ggplot2) Entire issue available at rweekly.org/2021-W42 (https://rweekly.org/2021-W42.html) Supplement Resources Type safety: https://en.wikipedia.org/wiki/Type_safety Eric's R development repository: https://github.com/rpodcast/rdevprojects Visual Studio Code R extension: https://github.com/REditorSupport/vscode-R Looking to provide feedback on this episode and the podcast in general? Feel free to get in touch with Mike (@mike_ketchbrook (https://twitter.com/mike_ketchbrook)) or Eric (@theRcast (https://twitter.com/rpodcast)) on Twitter!

Using Animal Crossing data with the Google Vision API and machine learning, the latest Shiny developer series with Nick Strayer, and ensuring robust database transactions in Shiny Episode Links This week's curator: Tony Elhabr ([@TonyElHabr] Everybody Loves Raymond: Running Animal Crossing Villagers through the Google Vision API (https://mdneuzerling.com/post/everybody-loves-raymond-running-animal-crossing-villagers-through-the-google-vision-api/) Shiny Developer Series Episode 21 (https://www.youtube.com/watch?v=84Vg7HKzd2E): RStudio software engineer Nick Strayer returns to share how he arrived to RStudio and motivations behind the new Shiny App Stories. Shiny in Production: Database Transactions (https://roh.engineering/posts/2021/06/shiny-in-production-database-transactions/) Entire issue available at rweekly.org/2021-W24 (https://rweekly.org/2021-W24.html)

In episode 21 of the Shiny Developer Series, I have the pleasure of welcoming back the newest member of the Shiny team, Nick Strayer! We discuss the road Nick traveled to join RStudio full time, as well as the motivation behind the terrific Shiny App Stories, complete with a hands-on demonstration of new features in Shiny 1.6 such as bindCache and dynamic theming in the fun explore your weather application. All of that plus Nick's perspectives on the growing Shiny ecosystem and creating powerful data visualizations make this a must-see episode!Resources mentioned in the episodeShiny App Stories example - The "Why" documentation, plus demonstrations of new and advanced features in the context of real-world applications.bindCache() - To speed up your app's reloading of previously accessed data. Dynamic theming with bslib - bslib helps you theme your app really easily. session objectgetCurrentOutputInfoData visualization innovators Nick follows: Nadieh Bremer (@NadiehBremer), Shirley Wu (@sxywu), Amelia Wattenberger (@Wattenberger).Episode Timestamps00:00:00 Episode Introduction 00:06:15 Nick's journey since episode 5 00:08:10 Shiny app stories - an experimental form of documentation. Most documentation focuses on the How to do something, Shiny App Stories focuses on the Why 00:13:15 App Stories in action 00:16:25 bindCache() discussion on speeding up your Shiny app 00:22:57 Dynamic theming with {bslib} 00:27:00 The usefulness of the session object in an Shiny app 00:32:30 Including web-technologies (like custom js, css, incorporating better design philosiphies) in your Shiny app 00:39:50 On the Shiny Ecosystem. Nick only recently moved from being an active Shiny developer to being on the core-Shiny team itself 00:43:35 On Creating great data visualizations and offering data consumers an excellent user experience 00:56:25 What's the best way to give feedback to the Shiny team? 01:05:22 Episode wrapup

A brand new season of the Shiny Developer Series kicks off with RStudio's chief scientist Hadley Wickham! Hadley joins Eric in episode 19 to discuss his exciting new book, Mastering Shiny. As author of many Tidyverse packages and long time contributor to the data science community, he has poured his wealth of experience into this book dedicated to helping you become a better Shiny developer. We talk about the origins of Shiny and advice for those just starting out. For those already familiar with Shiny we discuss debugging, how to level up your skills, and best practices for seeking help and contributing to the community.Resources mentioned in the episodeMastering Shiny (online)Advanced R: Second EditionR for Data ScienceEpisode Timestamps0:00 Episode introduction 2:05 Hadley's involvement with Shiny's early development 5:22 Writing Mastering Shiny 8:30 Shiny touches on data analysis alongside software engineering and programming 12:41 Best ways to get started with Shiny 14:53 Value of tidy evaluation with Shiny 19:41 Importance & challenge of reactivity 24:30 Getting help with Shiny 28:43 Becoming a better Shiny developer and collaborator 33:51 Shiny community engagement 38:12 Where to find Mastering Shiny 40:01 How to level-up your skills as a Shiny developer 41:53 Recap and closing remarks

In episode 12 of the Shiny Developer Series, we begin a multi-part series with RStudio software engineer on the Shiny team Barret Schloerke! In part 1 we learn more about Barret's journey to the Shiny team and take a deep dive into the very powerful reactlog framework to help users shed some light on what can be a confusing world of reactivity in their applications. Barret leads us through interactive demonstrations of reactlog applied to simple and complex applications to pinpoint various issues on reactive logic and the flow of information from inputs to outputs.Resources mentioned in the episode{rbokeh} - R interface for Bokeh: hafen.github.io/rbokeh{trelliscopejs} - Create interactive trelliscope displays: hafen.github.io/trelliscopejs{autocogs}: github.com/schloerke/autocogs{reactlog} - Provides a visual insight into that black box of Shiny reactivity: rstudio.github.io/reactlogDemos: (Launch reactlog: cmd + F3 or ctrl + f3)shiny::runApp("reactlog/reactlog-pythagorus.R")shiny::runApp("reactlog/reactlog-pythagorus-broken.R")shiny::runApp("reactlog/reactlog-cranwhales.R")shiny::runApp("reactlog/reactlog-anti-pattern.R")Episode Timestamps0:00 - Intro 0:42 - Barret's background, how he got started with R, Shiny, and RStudio. 3:41 - Bokey, Trelliscope, Ryan Hafen 4:36 - Autocogs 5:56 - Starting with RStudio 7:31 - Introduction to reactlog 9:31 - Demonstration of reactlog 10:51 - How reactlog can help diagnose issues 11:11 - Diagnosing a Shiny app's output example 13:30 - Demo of using reactlog with a larger application 14:31 - Zooming in example 15:00 - Using the search bar 17:25 - Finding anti-patterns 23:27 - Wrapup

In episode 13 of the Shiny Developer Series, we continue our conversation with RStudio software engineer Barrett Schloerke to highlight how you can integrate Shiny apps with custom APIs written in R via the plumber package! You'll see awesome demonstrations of the key features that are part of the brand new plumber 1.0 release, including brand new serializers and parsers for custom objects, a new tidy API compliant with magrittr pipelines, utilizing asynchronous execution, and more.Resources mentioned in the episodeplumber allows you to create a web API by merely decorating your existing R source code with roxygen2 style comments. Site: https://www.rplumber.io/Demos:NEW - Hex logo and website!NEW - pipe-able programatic interface Demo: plumb(dir = "plumber/pipe") %>% pr_run()NEW - POST body parsing Process incoming POST body dataEx: HTML forms, multipart forms, csv, tsv, json, yaml, feather and rds.Like serializers, register new POST body parsersSite: https://www.rplumber.io/reference/parsers.htmlMore Serializers! Serialize outgoing route dataEx: plain text, json, yaml, csv, tsv, rds, featherNEW - Register image serializers: svg, tiff, bmp, pdf. (Pre existing: png, jpeg)Site: https://www.rplumber.io/reference/serializers.htmlNEW - Download return values as attachments! Site: https://www.rplumber.io/reference/as_attachment.htmlDemo: plumb_api("plumber", "16-attachment") %>% pr_run()NEW - Async / promises Demo: plumb("plumber/plumber-future.R") %>% pr_run()NEW - API UIs (rapidoc) Register new User Interfaces to look at your APIDemo: plumb(dir = "plumber/rapidoc") %>% pr_run()Thank you to Bruno Tremblay (@meztez) for his heavy contributions to plumber!Recent conference talks about plumber: Democratizing R with plumber APIs (James Blair): rstudio.com/resources/rstudioconf-2019/democratizing-r-with-plumber-apisPractical plumber patterns (James Blair): rstudio.com/resources/rstudioconf-2020/practical-plumber-patterns/Bike Prediction example application with plumber API and Shiny: solutions.rstudio.com/tour/bike_predict/Episode Timestamps0:00 - Intro 1:14 - Introduction to plumber 4:14 - Example of plumber API 7:14 - Pipeable interface for plumber 9:19 - plumber's new hex logo! 9:24 - Serializers in plumber 13:04 - Parsers in plumber 14:30 - as_attachment for serializers 15:50 - Demo of downloading an attachment from API 16:07 - A consistent way to check for plumber APIs with available_apis() 18:50 - Async processing in plumber 24:23 - Demo of the plumber documentation UI 29:20 - Example of decoupling data source from Shiny app 29:50 - Episode wrapup

We have another fun installment of the Shiny Developer Series in episode 15! Our guest is statistical programmer and data scientist Maya Gans, and she tells us about her unique journey to R, her experience as a summer intern at RStudio, and the ways she has wielded some magical integrations of Shiny and javascript to create powerful applications in life sciences. Plus you will not want to miss the inside story behind the shinykeyboard widget!Resources mentioned in the episodeTidyBlocks (A block-based tool for teaching basic data science): [https://tidyblocks.tech/](tidyblocks.tech)shinyBody A custom Shiny input widget built with HTML and CSS that lets you select a body part and will return that body part's name.You can also color limbs based on data by specifying high and low color values: [https://github.com/MayaGans/shinyBody](github.com/MayaGans/shinyBody)JavaScript for Data Science: [https://js4ds.org/](js4ds.org)TidyCDISC application demonstration at the R/Medicine 2020 Virtual Conference: [https://www.youtube.com/watch?v=QeHSjw-vU3U](youtube.com/watch?v=QeHSjw-vU3U)Interactive web-based data visualization with R, plotly, and Shiny: [https://plotly-r.com/](plotly-r.com)timevis R package for creating timeline visualizations: [https://daattali.com/shiny/timevis-demo/](daattali.com/shiny/timevis-demo)ggkeyboard: [https://github.com/sharlagelfand/ggkeyboard](github.com/sharlagelfand/ggkeyboard)shinykeyboard R package to create an on-screen keyboard as a custom R Shiny input binding: [https://github.com/willdebras/shinykeyboard](github.com/willdebras/shinykeyboard)dreamRs Shiny gallery: [http://shinyapps.dreamrs.fr/](shinyapps.dreamrs.fr)Episode Timestamps0:00 Episode introduction 4:30 TidyBlocks tidyblocks.tech. A block-based tool for teaching basic data science. 7:00 Garrick Aden-Buie, https://www.garrickadenbuie.com/ 7:45 shinyBody. Everyone asks, “What are good ways to level up on R and Shiny?”, the shinyBody Shiny app is a relatively simple, focused Shiny app that helps you get JavaScript started talking to R. 14:20 David Granjon's Outstanding User Interfaces 14:35 R + Shiny for JS Visualizations. JavaScript for Data Science, website. Find it on Google Books, amazon 15:25 tidyCDISC Shiny App. tidyCDISC CDISC is a file format for clinical trials. This app helps you explore your CDISC data, following common patterns and at least as a first pass, helping you produce standard tables and figures the FDA will want to see. 17:18 golem, not just a nice tool for Shiny app development , but also for multi-developer, collaborative Shiny app development. “golem: If you're working with a team of people, I highly recommend it, for easier collaboration.” 19:00 CDISC table generator. 25:20 plot.ly in shiny apps. Carson's Book on ploy.ly with R. 27:15 shiny timevis by Dean Attali. On github. 29:15 Extending Sharla Gelfand's ggkeyboard into shinykeyboard made with Will Bonnell. A visual keyboard, a tool for added accessibility with R. 33:50 “What advice do you have for Shiny developers in our audience who want to take their skills to the next level?” 36:20 Episode conclusion

We conclude our multi-part series with RStudio software engineer Barret Schloerke with an in-depth look at the learnr package and how Shiny plays a huge role in powering the many features and extensibility available! Barret walks us through two showcases of learnr in action with the RStudio primer tutorials as well as the eye-catching naniar missing values tutorial by Allison Horst. Plus we get a preview of the great features coming up in the next release, and advice for Shiny developers looking to bring their skills to the next level.Resources mentioned in the episodelearnrThe learnr package makes it easy to turn any R Markdown document into an interactive tutorial. Tutorials consist of content along with interactive components for checking and reinforcing understanding.Site: https://rstudio.github.io/learnr/Demos:RStudio Primers: https://rstudio.cloud/learn/primersAllison Horst Post: https://education.rstudio.com/blog/2020/05/learnr-for-remote/Demo: https://allisonhorst.shinyapps.io/missingexplorer/Source: https://github.com/allisonhorst/explore-naSortable Site: https://rstudio.github.io/sortable/Demo: https://rstudio.github.io/sortable/tutorials/tutorial_question_rank.htmlEpisode Timestamps0:00- Episode Introduction 0:48- Introduction to learnr 2:10- Examples of learnr tutorials, rstudio.com/learn/primers 5:26- A very nice learnr tutorial example from Alison Horst 7:10- Getting started with learnr 9:10- {sortable} for questions that require ranking/sorting questions. 12:40 - Working on multi-language support. Including SQL, Python, and more. 14:16 - Advice for Shiny users 18:34 - Episode wrap-up

Plots with GitHub Actions, and major updates to {renv} and {fastai} Episode Links This week's curator: Batool Almazrouq (https://twitter.com/batool664) Automatic Rendering of a Plot with GitHub Actions (https://amitlevinson.com/blog/automated-plot-with-github-actions) {renv} 0.12.5 (https://cran.r-project.org/package=renv): Project Environments {fastai} 2.0.2 (https://cran.r-project.org/package=fastai): Interface to fastai Supplemental Resources GitHub Actions: built by you, run by us (https://github.blog/2018-10-17-action-demos) R-Podcast Episode 32: RStudio's Big Move and Kevin Ushey (https://r-podcast.org/32) Fully containerized R dev environment with Docker, RStudio, and VS-Code (https://youtu.be/4wRiPG9LM3o?t=389) What does it mean to freeze or unfreeze a model? (https://stats.stackexchange.com/questions/393168/what-does-it-mean-to-freeze-or-unfreeze-a-model)

About this episode Single source publishing, rainbow parentheses, and VisiumExperiment Episode Links This week's curator: Robert Hickman (@robwhickman (https://twitter.com/robwhickman)) Single-source publishing for R users (https://masalmon.eu/2020/11/06/single-source-publishing-r/) RStudio 1.4 Preview: Rainbow Parentheses (https://blog.rstudio.com/2020/11/04/rstudio-1-4-preview-rainbow-parentheses/) Using VisiumExperiment at spatialLIBD package (http://LieberInstitute.github.io/rstatsclub/2020/11/06/using-visiumexperiment-at-spatiallibd-package/) Entire issue available at rweekly.org/2020-45 (https://rweekly.org/2020-45) Supplement Links https://github.com/maelle/bspagedjs https://bookdown.org/

The Shiny Developer Series is back! In our first session of 2020, we are joined by professional educator and data scientist Mine Cetinkaya-Rundel to get the inside story of the newly updated Shiny Dev Center (including a major revision of the Shiny Gallery) and the insights RStudio gained from the Shiny Contest. Also Mine shares her advice on developing educational material for Shiny users and where she sees future opportunities in this evolving space.ResourcesShiny Gallery: shiny.rstudio.com/galleryShiny Tutorials: shiny.rstudio.com/tutorialReprex guide for Shiny questions on RStudio Community: community.rstudio.com/100012020 Shiny Contest information: blog.rstudio.com/2020/02/12/shiny-contest-2020-is-hereMastering Shiny by Hadley Wickham: mastering-shiny.orgEpisode Timestamps00:56 Mine Introduction. 03:01 Shiny Gallery - walkthrough and recent revamp. 04:15 Shiny Demos - live examples and deep-dive into shiny's features. 05:20 Shiny User Showcase - A large set of example shiny apps, by the Shiny community. Including code on github, and interactive code on rstudio.cloud. 06:10 Shiny Contest 2019 lead to the revamp of the showcase. 09:00 Example running an app on the Shiny Showcase interactively with rstudio.cloud. 12:40 Shiny Gallery walkthrough - Mine's learnings from reviewing the Shiny apps on the gallery. There's a lot to learn from, but Mine highlighted just a few: 13:40 1. BYOD Apps - Bring your own data shiny app best practices. 14:42 2. App Walkthroughs and jintrojs package. iSEE Shiny App. 17:15 3. Apps that don't look like Shiny apps. 17:30 Example 1. 69 Love Songs by the Magnetic Fields. 18:25 Example 2. Uber explorer app - another example that doesn't look like a standard shiny app. 19:04 Example 3. CRAN Explorer. 19:55 Example 4. Hex memory game. An example of a game Shiny app. 22:15 Teaching and Educational Materials for Shiny - Shiny development has its own set of challenges and Mine spends a lot of time thinking about teaching Shiny. 23:45 Learn Shiny tutorial - a nice short intro to Shiny. Includes written articles, videos, and code examples. shiny.rstudio.com/tutorial. 24:30 Asking good questions about the issues you're having with your Shiny app. What are good workflows for seeking help? Barret's Shiny debugging and reprex guide http://community.rstudio.com/t/10001 26:17 Materials for intermediate Shiny users. Articles on shiny.rstudio.com, workshop and conference videos, and a call to the Shiny Community. 28:00 Also for advanced Shiny developers, Hadley's Mastering Shiny book. Coming late 2020 mastering-shiny.org. 30:10 Shiny Contest 2020 - learnings from last year's contest, and advice to folks submitting to the next contest. https://blog.rstudio.com/2020/02/12/shiny-contest-2020-is-here/ 39:12 Shiny Dev Series Outtro