Podcasts about tidyverse

In this episode of R Weekly Highlights: We have a six-month follow-up perspective from an early Positron user, how the current landscape of AI tools perform when learning the ropes with the Tidyverse, and how you can create your first Observable plot while using R for data munging.Episode LinksThis week's curator: Jon Carroll - @jonocarroll@fosstodon.org (Mastodon) & @jonocarroll.fosstodon.org.ap.brid.gy (Bluesky) & @carroll_jono (X/Twitter)Positron: current joys and painsLearning the tidyverse with the help of AI toolsObservable for R usersEntire issue available at rweekly.org/2025-W15Supplement ResourcesPositron +1e https://open-vsx.org/extension/grrrck/positron-plus-1-eVanishing Gradients episode 47 (The Great Pacific Garbage Patch of Code Slop with Joe Reis) https://vanishinggradients.fireside.fm/47Observable color palette viewer https://observablehq.com/plot/features/scales#color-scalesObservable Plots (R/Pharma 2024 Workshop Series) https://www.youtube.com/watch?v=M6fP68XnacMSupporting 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 OCRemixSunny Side Up - Yoshi's Island DS - ZackParrish - https://ocremix.org/remix/OCR04558Costa Del Sol DANCE - Final Fantasy VII - Posu Yan - https://ocremix.org/remix/OCR00095

Send us a textWhy has SAS been the cornerstone of clinical trials for decades, and what is causing the shift to R now? Join us on "Transformation in Trials" as we explore this pivotal transition with Sunil Gupta, a seasoned programmer who has navigated both worlds. Sunil elaborates on SAS's long-standing dominance due to its robust programming capabilities and ease of use for FDA reviewers. However, the landscape is changing as R garners attention for its graphical prowess and collaborative potential. The conversation highlights the growing trend of new graduates versed in R and Python, which alleviates the shortage of SAS programmers and signifies a modernization wave in clinical trials, ultimately aiming to accelerate drug development.Our discussion takes a deep dive into the collaborative spirit driving this transition, particularly through initiatives like Pharmaverse. This specialized extension of Tidyverse is designed to optimize clinical data workflows within the pharmaceutical industry. Sunil shares insights into how clinical programming is evolving, focusing on standardized data models and the unification of CDISC standards. The conversation underscores the importance of collaboration and resource sharing, allowing organizations to tackle complex challenges efficiently and improve patient outcomes while adapting to R's open-source environment and its growing acceptance in pharmaceutical submissions.Transitioning from SAS to R is not just about adopting a new tool; it's about mastering new skills and embracing change. Sunil discusses the challenges he faced when learning R, from understanding its functional approach to navigating intricate syntax. He offers personal anecdotes that reflect his journey and the broader industry shift, emphasizing the importance of validation processes and resource optimization. As we conclude this episode, we express gratitude for the platform to discuss these transformative changes and invite listeners to engage with us on future topics, continuing to share success stories that inspire more organizations to embrace the power of R.________Reach out to Sam Parnell and Ivanna RosendalJoin the conversation on our LinkedIn page

Creating retro-gaming sprites rendered from the comforts of R? Yes we can! Plus an honest take on the utility of Github's Copilot Workspace in the context of package development, and taking the concept of code trees to another level with treesitter.Episode LinksThis week's curator: Ryo Nakagawara - @RbyRyo@mstdn.social (Mastodon) & @RbyRyo) (X/Twitter)Tile-style sprite delightSome thoughts after a trial run of GitHub's Copilot WorkspaceExtracting names of functions defined in a script with treesitterEntire issue available at rweekly.org/2024-W30Supplement Resourcestree-sitter-r https://github.com/r-lib/tree-sitter-rShiny.telemetry 0.3.0 https://www.appsilon.com/post/shiny-telemetry-0-3-0-updateIntroduction to R with the Tidyverse https://introduction-r-tidyverse.netlify.app/session1_notesSupporting 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.info Get in touch with us on social mediaEric Nantz: @rpodcast@podcastindex.social (Mastodon) and @theRcast (X/Twitter)Mike Thomas: @mikethomas@fosstodon.org (Mastodon) and @mikeketchbrook (X/Twitter) Music credits powered by OCRemixMoonlight Vibin' - Mega Man X5 - DCT - https://ocremix.org/remix/OCR02053Forest Through the Trees - Shea's Violin - Final Fantasy Mystic Quest - https://ocremix.org/remix/OCR04484

Tidyverse, ggplot2, and the secret to a tech company's longevity: Hadley Wickham talks to Jon Krohn about Posit's rebrand, Tidyverse and why it needs to be in every data scientist's toolkit, and why getting your hands dirty with open-source projects can be so lucrative for your career. This episode is brought to you by Intel and HPE Ezmeral Software (https://bit.ly/hpeintel). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. In this episode you will learn: • All about the Tidyverse [04:46] • Hadley's favorite R libraries [17:10] • The goal of Posit [30:29] • On bringing multiple programming languages together [36:02] • The principles for a long-lasting tech company [52:10] • How Hadley developed ggplot2 [55:24] • How to contribute to the open-source community [1:05:43] Additional materials: www.superdatascience.com/779

How a novel blend of automation and the YouTube API formed a new R-Ladies meetup recording dashboard built entirely with R, the momentum of webR continues with a fantastic guide to create a serverless Shiny app, and a new challenger in the world of high-performance data manipulation libraries arrives. Episode Links This week's curator: Jon Calder (@jonmcalder (https://twitter.com/jonmcalder)) (Twitter) Using flexdashboard to create a GitHub Actions-powered YouTube feed (https://ivelasq.rbind.io/blog/automated-youtube-dashboard/) Building Serverless Shiny Apps with webR: A Step-by-Step Guide (https://hypebright.nl/index.php/en/2023/07/25/building-serverless-shiny-apps-with-webr-a-step-by-step-guide/) Cookbook Polars for R (https://github.com/ddotta/cookbook-rpolars) Cookbook to provide solutions to common tasks and problems in using Polars with R. A side-by-side comparison of polars, R base, dplyr, tidyr and data.table packages. Entire issue available at rweekly.org/2023-W32 (https://rweekly.org/2023-W32.html) Supplement Resources Tube Archivist - Your self-hosted YouTube media server https://www.tubearchivist.com webR code extension for HTML Quarto documents https://github.com/coatless/quarto-webr Into the webR-verse (Bob Rudis presentation at the 2023 New York R Conference) https://www.youtube.com/watch?v=inpwcTUmBDY tidypolars - Provide the functionalities of Polars with the syntax of the Tidyverse https://www.tidypolars.etiennebacher.com 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)

A few strict checks offered in R 4.3.0, measuring and writing performant code in the Tidyverse, and a please for indenting your code with (more) spaces. Episode Links This week's curator: Eric Nantz - @theRcast (https://twitter.com/theRcast) (Twitter) & @rpodcast@podcastindex.social (https://podcastindex.social/@rpodcast) (Mastodon) What's new in R 4.3.0? (https://www.jumpingrivers.com/blog/whats-new-r43/) Writing performant code with tidy tools (https://www.tidyverse.org/blog/2023/04/performant-packages/) On Indentation in R (https://www.hiddenelephants.co.uk/Blog/on-indentation-in-R.html) Entire issue available at rweekly.org/2023-W17 (https://rweekly.org/2023-W17.html) Supplement Resources Changes in R 4.3.0: https://stat.ethz.ch/R-manual/R-devel/doc/html/NEWS.html A Question A Day Twitter account https://twitter.com/data_question Advanced R- Measure Performance https://adv-r.hadley.nz/perf-measure.html Supporting the show Use the contact page at https://rweekly.fireside.fm/contact to send us your feedback Find R-Weekly Highlights on the Podcast Index https://podcastindex.org/podcast/1062040 Get a New Podcast App and send us a boost directly! 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)

One of the common themes seen throughout the Shiny Developer Series is that effective Shiny development is much more than just getting an application to work! Other important considerations include applying Shiny to high-profile projects, ensuring a production-grade code base, and even building robust tooling to assist with development. I have the pleasure of discussing these with Appsilon software engineer and Shiny frontend developer Pedro da Silva! You will hear Pedro's practical advice on the many developer-friendly packages and tools he uses for production Shiny development, a detailed walkthrough of his (Shiny contest) award-winning Shiny Decisions application, and his recommendations for taking your Shiny development skills to the next level.Resources mentioned in the episodePedro's website with links to posts and webinnars: https://www.pedrocsilva.comAppsilon: https://appsilon.comShiny Decisions repo: https://github.com/pedrocoutinhosilva/shiny.decisionsDeployed Shiny Decisions app: https://sparktuga.shinyapps.io/ShinyDecisionsR6 chapter from Advanced R: adv-r.hadley.nz/r6.html{glue} for interpreted string literals: https://glue.tidyverse.org/{tidymodules}: https://opensource.nibr.com/tidymodules/index.html{sass} for R and Shiny: https://rstudio.github.io/sass/index.html{bslib}: https://rstudio.github.io/bslib/John Coene's "Javascript for R" book: https://book.javascript-for-r.com/David Granjon's "Outstanding Shiny UI" book: https://unleash-shiny.rinterface.com/{renv}: https://rstudio.github.io/renv/articles/renv.html{testthat}: https://testthat.r-lib.org/{shinyloadtest}: https://rstudio.github.io/shinyloadtest/Tidyverse style guide: https://style.tidyverse.org/An lintr, which performs automated checks to confirm that you https://appsilon.com/conform to the style guide, https://github.com/jimhester/lintrMastering Shiny: https://mastering-shiny.org/Pedro's recommended Chrome extensions for development: Resolution Test: Test web pages in different screen resolutionsColorPick Eyedropper: A zoomed eyedropper & color chooser toolScreenshotting: Web page screen captureCSS Peeper: Extract CSS and build beautiful styleguidesEpisode Timestamps00:00:05 Episode Introduction 00:02:49 Appsilon, Shiny consulting 00:07:49 The wonderful 'black magic' of Shiny 00:09:55 Custom Shiny apps in the enterprise. Number one theme: migrating from excel 00:17:45 Demo of Shiny app game Shiny Decisions 00:22:55 A code walkthrough of Shiny Decisions 00:32:55 On styling Shiny Decisions 00:50:45 The value of learning a little javascript to improve your Shiny apps 00:51:55 Book recommendations for integrating Javascript into your Shiny app and improving UI 00:52:55 Pedro on jQuery for Shiny 00:56:05 Advice for building Shiny apps in production 01:10:05 Advice for people seeking a career in data science with R and Shiny

One of the common themes seen throughout the Shiny Developer Series is that effective Shiny development is much more than just getting an application to work! Other important considerations include applying Shiny to high-profile projects, ensuring a production-grade code base, and even building robust tooling to assist with development. I have the pleasure of discussing these with Appsilon software engineer and Shiny frontend developer Pedro da Silva! You will hear Pedro's practical advice on the many developer-friendly packages and tools he uses for production Shiny development, a detailed walkthrough of his (Shiny contest) award-winning Shiny Decisions application, and his recommendations for taking your Shiny development skills to the next level. Resources mentioned in the episode Pedro's website with links to posts and webinnars: https://www.pedrocsilva.com Appsilon: https://appsilon.com Shiny Decisions repo: https://github.com/pedrocoutinhosilva/shiny.decisions Deployed Shiny Decisions app: https://sparktuga.shinyapps.io/ShinyDecisions R6 chapter from Advanced R: adv-r.hadley.nz/r6.html (https://adv-r.hadley.nz/r6.html) {glue} for interpreted string literals: https://glue.tidyverse.org/ {tidymodules}: https://opensource.nibr.com/tidymodules/index.html {sass} for R and Shiny: https://rstudio.github.io/sass/index.html {bslib}: https://rstudio.github.io/bslib/ John Coene's "Javascript for R" book: https://book.javascript-for-r.com/ David Granjon's "Outstanding Shiny UI" book: https://unleash-shiny.rinterface.com/ {renv}: https://rstudio.github.io/renv/articles/renv.html {testthat}: https://testthat.r-lib.org/ {shinyloadtest}: https://rstudio.github.io/shinyloadtest/ Tidyverse style guide: https://style.tidyverse.org/ An lintr, which performs automated checks to confirm that you https://appsilon.com/conform to the style guide, https://github.com/jimhester/lintr Mastering Shiny: https://mastering-shiny.org/ Pedro's recommended Chrome extensions for development: Resolution Test (https://chrome.google.com/webstore/detail/resolution-test/idhfcdbheobinplaamokffboaccidbal): Test web pages in different screen resolutions ColorPick Eyedropper (https://chrome.google.com/webstore/detail/colorpick-eyedropper/ohcpnigalekghcmgcdcenkpelffpdolg): A zoomed eyedropper & color chooser tool Screenshotting (https://chrome.google.com/webstore/detail/screenshotting-full-page/pojgkmkfincpdkdgjepkmdekcahmckjp): Web page screen capture CSS Peeper (https://chrome.google.com/webstore/detail/css-peeper/mbnbehikldjhnfehhnaidhjhoofhpehk): Extract CSS and build beautiful styleguides Episode Timestamps 00:00:05 (https://youtube.com/watch?v=wGfYYa1rfbg&t=5s) Episode Introduction 00:02:49 (https://youtube.com/watch?v=wGfYYa1rfbg&t=169s) Appsilon, Shiny consulting 00:07:49 (https://youtube.com/watch?v=wGfYYa1rfbg&t=469s) The wonderful 'black magic' of Shiny 00:09:55 (https://youtube.com/watch?v=wGfYYa1rfbg&t=595s) Custom Shiny apps in the enterprise. Number one theme: migrating from excel 00:17:45 (https://youtube.com/watch?v=wGfYYa1rfbg&t=1065s) Demo of Shiny app game Shiny Decisions 00:22:55 (https://youtube.com/watch?v=wGfYYa1rfbg&t=1375s) A code walkthrough of Shiny Decisions 00:32:55 (https://youtube.com/watch?v=wGfYYa1rfbg&t=1975s) On styling Shiny Decisions 00:50:45 (https://youtube.com/watch?v=wGfYYa1rfbg&t=3045s) The value of learning a little javascript to improve your Shiny apps 00:51:55 (https://youtube.com/watch?v=wGfYYa1rfbg&t=3115s) Book recommendations for integrating Javascript into your Shiny app and improving UI 00:52:55 (https://youtube.com/watch?v=wGfYYa1rfbg&t=3175s) Pedro on jQuery for Shiny 00:56:05 (https://youtube.com/watch?v=wGfYYa1rfbg&t=3365s) Advice for building Shiny apps in production 01:10:05 (https://youtube.com/watch?v=wGfYYa1rfbg&t=4205s) Advice for people seeking a career in data science with R and Shiny

In this episode, we talk with educational consultant, data scientist, book author, podcast host, and former educational psychologist Ryan Estrellado about living in the Venn diagrams of overlapping professional communities and finding your (our) place in those intersections. We talk about practical strategies for working with educators who have a wide variety of interests in data and specifically tools for data analysis, and about breaking down common misconceptions about data analysis or data science as it can be used to answer real questions in local educational settings. Although we had planned to focus the episode on Ryan's new book, we accidentally ended up spending an entire hour discussing about unusual professional trajectories and how data and coding have influenced all of us (for the better). Some day we will do another episode where we actually talk about Ryan's book, but in the meantime, we recommend that you go ahead and check it out! The content is truly accessible to all educators, wherever you happen to be in terms of your data journey (whether that journey was embarked upon voluntarily or otherwise). Check out the link below to get a 20% off code for the book! Abbreviations: IDE: Integrated development environment https://www.codecademy.com/article/what-is-an-ide Show notes: Go to ryanestrellado.com to download a free chapter of The K–12 Educator's Data Guidebook and a 20% off code The K-12 Educator's Data Guidebook: Reimagining Practical Data Use in Schools Donuts in the Lounge: A Podcast for Educators Follow on Twitter & Instagram @ry_estrellado Data Science in Education using R (free open-source book with hands-on activities to learn R using real-world education contexts): https://datascienceineducation.com/ Strategic Data Project at Harvard: https://sdp.cepr.harvard.edu/home South County SELPA at the San Diego County Office of Education: https://www.sdcoe.net/special-populations/selpas/scselpa Chase Jarvis, Creative Calling https://www.creativelive.com/class/creative-calling-chase-jarvis/lessons/amplify-your-community About Practice podcast (Ryan Estrellado & Joshua Rosenberg): https://open.spotify.com/show/4TzYLKTen3ZiJxiiKdHAsa R Studio (free download): https://www.rstudio.com/products/rstudio/ Tidyverse: https://www.tidyverse.org/ Hadley Wickham's website and list of books: https://hadley.nz/ Julia Silge: https://juliasilge.com/about/ Kieran Healy: Data Visualization: A Practical Introduction https://socviz.co/ Rosh's favorite vending machine video: https://www.youtube.com/watch?v=mMW6JKNop1Y Music: Exploring The World by Vlad Gluschenko is licensed under a Creative Commons License. https://creativecommons.org/licenses/... https://soundcloud.com/vgl9 Support by RFM - NCM

Hugo speaks with Heather Nolis, Principal Machine Learning engineer at T-mobile, about what data science, machine learning, and AI look like at T-mobile, along with Heather's path from a software development intern there to principal ML engineer running a team of 15. They talk about: how to build a DS culture from scratch and what executive-level support looks like, as well as how to demonstrate machine learning value early on from a shark tank style pitch night to the initial investment through to the POC and building out the function; all the great work they do with R and the Tidyverse in production; what it's like to be a lesbian in tech, and about what it was like to discover she was autistic and how that impacted her work; how to measure and demonstrate success and ROI for the org; some massive data science fails!; how to deal with execs wanting you to use the latest GPT-X – in a fragmented tooling landscape; how to use the simplest technology to deliver the most value. Finally, the team just hired their first FT ethicist and they speak about how ethics can be embedded in a team and across an institution. Links Put R in prod (https://putrinprod.com/): Tools and guides to put R models into production Enterprise Web Services with Neural Networks Using R and TensorFlow (https://medium.com/tmobile-tech/enterprise-web-services-with-neural-networks-using-r-and-tensorflow-a09c1b100c11) Heather on twitter (https://twitter.com/heatherklus) T-Mobile is hiring! (https://www.t-mobile.com/careers) Hugo's upcoming fireside chat and AMA with Hilary Parker about how to actually produce sustainable business value using machine learning and product management for ML! (https://www.eventbrite.com/e/select-ml-project-where-value-is-not-null-tickets-284000161127?aff=hba)

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

Veerle van Leemput joins us to make the case for why you should be using R for production. In this episode you will learn: • Our shared powerlifting passion [2:47] • The stigma of using R [12:02] • What does Analytic Health do? [13:55] • How Analytic Health uses R [19:08] • Tidyverse [34:44] • Tools for API creation [37:09] Additional materials: www.superdatascience.com/491

Stevey's Blog Rants (https://steve-yegge.blogspot.com/2006/03/execution-in-kingdom-of-nouns.html) Tidyverse (https://www.tidyverse.org/) Codewars Java Kata (requires sign in and some Java homework) (https://www.codewars.com/kata/reviews/54a83d11e1288d7cd70001d6/groups/54b6e0b3ac3d54604b001320) Reddit: I found this during my first day in new job (https://www.reddit.com/r/programminghorror/comments/lr6ip1/i_found_this_during_my_first_day_in_new_job/) Reddit: Dutch electronic voting code base (https://www.reddit.com/r/programminghorror/comments/juqafi/dutch_electronic_voting_code_base/) CS50's Introduction to Computer Science (https://www.edx.org/course/cs50s-introduction-to-computer-science) Justice (https://www.edx.org/course/justice-2) Crash Course (https://thecrashcourse.com/) Fat Chance: Probability from the Ground Up (https://www.edx.org/course/fat-chance-probability-from-the-ground-up-2) Heidelberg Studentenkarzer (https://www.atlasobscura.com/places/heidelberg-studentkarzer) Harvard Business Review Podcasts (https://hbr.org/podcasts)

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

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 episode Mastering Shiny (online) (https://mastering-shiny.org) Advanced R: Second Edition (https://adv-r.hadley.nz) R for Data Science (https://r4ds.had.co.nz) Episode Timestamps 0:00 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=0m0s) Episode introduction 2:05 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=2m05s) Hadley's involvement with Shiny's early development 5:22 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=5m22s) Writing Mastering Shiny 8:30 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=8m30s) Shiny touches on data analysis alongside software engineering and programming 12:41 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=12m41s) Best ways to get started with Shiny 14:53 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=14m53s) Value of tidy evaluation with Shiny 19:41 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=19m41s) Importance & challenge of reactivity 24:30 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=24m30s) Getting help with Shiny 28:43 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=28m43s) Becoming a better Shiny developer and collaborator 33:51 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=33m51s) Shiny community engagement 38:12 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=38m12s) Where to find Mastering Shiny 40:01 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=40m01s) How to level-up your skills as a Shiny developer 41:53 (https://www.youtube.com/watch?v=PJsIO8C9xp0&t=41m53s) Recap and closing remarks

Hadley Wickham, chief scientist at RStudio and creator of the Tidyverse, discusses how R and its data science package the TidyVerse are used and created. Host Felienne speaks with Wickham about the design philosophy of the Tidyverse, and how it supports..

In order to measure what matters, it is important to have the data available to help. Sarah Lin is the Information Architect & Digital Librarian at RStudio, PBC, and is also a law librarian. RStudio wanted someone to help them manage their digital morass and to Marie Kondo their digital information. Is there anyone better than a law librarian with some tech skills to do just that? Sarah discusses what the R Programming language does, and how she got interested in the profession of statistical computing. While some may not see a direct link between being a law librarian and an R programmer, there are actually a number of skills librarians possess which make them well suited for data analytics. One skill is our ability to understand, clean, and organize information. For RStudios, the Chief Scientist, Hadley Wickam created Tidyverse which helps in handling the clean data tasks. And there are also resources like Shinyapps.io to help organize. Throw in a law librarian to have it all make sense and tell a story and you have a fantastic combination of skills and tool. To learn more about the R language check out: Carpentries.org education.rstudio.com Or go to Sarah Lin's website Information Inspirations Roy Sexton from Clark Hill lays out what law firm marketing does as opposed to what law firm business development does in the latest episode of Steve Fretzin's Be That Lawyer. Roy's advice of the "Rule of Three" when it comes to promoting yourself and your marketing products makes this a must-listen episode. Adam Smith, Esq. covers the new initiative by our friend Phil Flora and Leopard Solutions on ranking law firms by their vitality and resilience, not just once a year, but in real-time. Feeling the effects of COVID, the election, the environment, or the hundred other stressors in your life? Maybe take Prof. Eric Janssen's advice and put down your phone and go for a walk. Did you know there was a Pirate who was a 17th Century Anthony Bourdain? Marlene teaches Greg about this culinary outlaw, and also teaches him about breadfruit. Listen, Subscribe, Comment Please take the time to rate and review us on Apple Podcast. Contact us anytime by tweeting us at @gebauerm or @glambert. Or, you can call The Geek in Review hotline at 713-487-7270 and leave us a message. You can email us at geekinreviewpodcast@gmail.com. As always, the great music you hear on the podcast is from Jerry David DeCicca.

This episode, I'm speaking with Dr. Julie Lowndes of Openscapes. Don't learn R alone! Resources for you and your friends:  her online training on Github for Excel users;  the core (open and free) text behind R is R for Data Science;  a guide to The Tidyverse.  This is the paper on how the Ocean Health Index used GitHub not just to track their data and writing but also to improve the way they work together.  Openscapes, a platform for open science, and an example from a UMass lab using Github to lay out what they work on and how they work together.

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.io (http://r4ds.io) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on college tuition, diversity, and pay: github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-03-10 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-03-10) Julia Silge's Screencast (https://twitter.com/juliasilge/status/1237485609855225857) The tidymodels (https://cran.r-project.org/package=tidymodels) suite of packages is available on CRAN! Stephanie Spielman's Students (https://twitter.com/stephspiel/status/1239561076632694786)

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on Spotify songs: github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-21 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-21) Georgios Karamanis's Sound Wave Charts (https://twitter.com/geokaramanis/status/1221114929584988160) Cedric Scherer's cowplot poster (https://twitter.com/CedScherer/status/1220850707454144512) The cowplot (https://cran.r-project.org/package=cowplot) package is available on CRAN! So it patchwork (https://cran.r-project.org/package=patchwork)! This week's San Francisco tree data: github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-28/ (https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-28/) dplyr::filter(qAddress != "302x Octavia St Frontage East") Find me at rstudio::conf(2020L) (rstd.io/conf)! A function (https://twitter.com/tidypod/status/1221168489815314434) to calculate the distance from the rstudioconf hotel to a given point. Check out RBERT (https://github.com/jonathanbratt/RBERT) and RBERTviz (https://github.com/jonathanbratt/RBERTviz)! And my factory (https://cran.r-project.org/package=factory) package is on CRAN! Listen to the #DataFemme podcast (https://www.dikayodata.com/datafemme)!

Dr. Gina Merchant and I discuss everything from athleticism to tips on how to enjoy the upcoming RStudio Conference in San Francisco. Her story of becoming a confident data maven by learning the tidyverse is bound to inspire you. Like what you hear on #DataFemme? Support us on Patreon for exclusive perks from career-related content to conference discounts: www.patreon.com/datafemmeMusic by Benjamin Barshai

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on passwords: github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-14 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-14) Ian Bell's Bar Chart (https://twitter.com/Ian_Bellio/status/1217262136650387458) The cowplot (https://cran.r-project.org/package=cowplot) package is available on CRAN! Jake Kaupp's donut/dendogram (https://twitter.com/jakekaupp/status/1217558989996728325) The ggraph (https://cran.r-project.org/package=ggraph) package is available on CRAN! This week's Spotify song data: github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-21/ (https://github.com/rfordatascience/tidytuesday/tree/master/data/2020/2020-01-21/) Find me at rstudio::conf(2020L) (rstd.io/conf)!

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on Adoptable Dogs: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-12-17 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-12-17) This week's Christmas Music data: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-12-24 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-12-24) SPOILER WARNING, you may not want to read below before listening to the episode. Twas the first Tidy Tuesday, in 2018. And my R data options were getting quite lean. I'd plotted gas mileage by displacement and cyls, I'd tired of iris; from diamonds, no thrills. My columns were features, my rows observations. My plots weren't quite perfect (they lacked annotations). But I'd learned all I could from Garrett and Hadley, What I needed was data, and I needed it badly. Then R4DS Online Learning Community Announced a new R practice opportunity! They'd post a new dataset once every week And, most importantly, 'twould be unique! The goal was for learners from novice to whiz To use that new data for their own dataviz. And whether those vizes were bars, lines, or maps We'd share our R code (on github, perhaps). We'd try out new packages, practice and play, Then share in a tweet hashtag TidyTuesday. And the rstats community would add their advice. With new tips and tricks (don't worry, they're nice)! So I started to read tweets by @thomas_mock And I waited each Monday (around 2 o'clock). Then I'd download the new dataset csv, And read Thomas's tweet to see what it might be. "Here's comics! Here's Star Wars! Here's US tuition!" "Here's how NFL players are paid by position!" "Here's video games! Here's Roman bloodlines!" "Here's UFO sightings! And ratings of wine!" And my plots? They improved! With new themes and palettes. And Thomas kept posting brand new datasets. I heard Thomas proclaim as he tweeted his tweet, "It's Tidy Tuesday, y'all! Now go code something neat!"

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on the New Zealand Bird of the Year: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-11-19 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-11-19) Julia Watzek's Waffle Chart (https://twitter.com/watzoever/status/1198698674769006592) Edgar Zamora's Waffle Chart (https://twitter.com/Edgar_Zamora_/status/1197677132270338048) The waffle (https://github.com/hrbrmstr/waffle) package is available on CRAN, but I recommend the dev version. Torsten Sprenger's bar-chart race (https://twitter.com/spren9er/status/1198008656241057795) The gganimate (https://cran.r-project.org/package=gganimate) package is available on CRAN. This week's Student Loan data: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-11-26 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-11-26) Check out the patchwork (https://patchwork.data-imaginist.com/index.html) package!

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on SQUIRRELS!: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-29 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-29) Maggie Sogin's Chord Diagram (https://twitter.com/MaggieSogin/status/1189132605754658817) The circlize (https://cran.r-project.org/package=circlize) package is available on CRAN. Also check out the chorddiag (https://github.com/mattflor/chorddiag) package on github. Cédric Sherer's gorgeous plots (https://twitter.com/CedScherer/status/1190284257324916736) (click through the retweet for more plots) The ggpointdensity (https://cran.r-project.org/package=ggpointdensity) package is available on CRAN. Interactive web-based data visualization with R, plotly, and shiny by Carson Sievert (https://plotly-r.com/maps.html) This week's data, bike and walk commutes: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-11-05 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-11-05) Code for cleaning the commute cities is available in this gist (https://gist.github.com/jonthegeek/e584dcc9e9b7c0537663eb97697763c7) See me at the Washington DC R Conference (https://dc.rstats.ai/)!

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on horror movies: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-22 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-22) David Smale's Blood Chart (https://twitter.com/committedtotape/status/1187109093003223040) Evan Barba's interactive plots (https://twitter.com/ewBarba/status/1187303627448209408) Interactive web-based data visualization with R, plotly, and shiny by Carson Sievert (https://plotly-r.com/maps.html) This week's data, SQUIRRELS!: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-29 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-29) Let me know if you play with RBERT (https://github.com/jonathanbratt/RBERT) See me at the Washington DC R Conference (https://dc.rstats.ai/)!

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on fuel efficiency: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-15 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-15) Colin Fay's Shiny app (https://twitter.com/_ColinFay/status/1184206856924868608) Check out golem (https://cran.r-project.org/package=golem) on CRAN! Georgios Karamanis's making-of: twitter.com/geokaramanis/status/1186001102724063232 (https://twitter.com/geokaramanis/status/1186001102724063232) and his viz: twitter.com/geokaramanis/status/1184696827326713856 (https://twitter.com/geokaramanis/status/1184696827326713856) Jayslen Serrano's spooky version: twitter.com/SerranoJayslen/status/1184345403946192896 (https://twitter.com/SerranoJayslen/status/1184345403946192896) Christian Burkart's tutorial: twitter.com/Christi58451746/status/1185668189172256771 (https://twitter.com/Christi58451746/status/1185668189172256771) Cédric Scherer's animations: twitter.com/CedScherer/status/1186335139925757952 (https://twitter.com/CedScherer/status/1186335139925757952) This week's data, horror movies: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-22 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-22) See me at the Washington DC R Conference (https://dc.rstats.ai/)!

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on International Powerlifting: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-08 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-08) Christian Burkhart's visualization: twitter.com/Christi58451746/status/1182024124115361794 (https://twitter.com/Christi58451746/status/1182024124115361794). Check out his tutorials at ggplot2tutor.com (https://ggplot2tutor.com/) Eric Ekholm's first-ever submission: twitter.com/ekholm_e/status/1183929391409221632 (https://twitter.com/ekholm_e/status/1183929391409221632) Kelly Luis's ridgelines: twitter.com/kelly_luis1/status/1181596849452519424 (https://twitter.com/kelly_luis1/status/1181596849452519424) The ggridges (https://CRAN.R-project.org/package=ggridges) package is available on CRAN! My audio... plot? ipf_music.R (https://github.com/jonthegeek/dataviz/blob/master/tidytuesday/2019-41/ipf_music.R) Install the devoutaudio (https://github.com/coolbutuseless/devoutaudio) package from (github.com/coolbutuseless)[https://github.com/coolbutuseless/] This week's data, Big mtcars: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-15 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-15) See me at the Washington DC R Conference (https://dc.rstats.ai/)!

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data on Pizza: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-01 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-01) David Smail's visualization: https://twitter.com/committedtotape/status/1179527075897757696 (https://twitter.com/committedtotape/status/1179527075897757696) Georgios Karamanis's making-of video: https://twitter.com/geokaramanis/status/1180402230261932032 (https://twitter.com/geokaramanis/status/1180402230261932032) Robert Walker's Rmarkdown doc: https://twitter.com/PieRatio/status/1179666251997560832 (https://twitter.com/PieRatio/status/1179666251997560832) The ggiraph (https://CRAN.R-project.org/package=ggiraph) package is available on CRAN! The rayshader (https://CRAN.R-project.org/package=rayshader) package is available on CRAN! This week's data on Powerlifting: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-08 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-08) Help me gather NLP data at http://bit.ly/nlptrains Check out the R-Podcast (https://r-podcast.org/)!

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-24 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-24) Joshua Feldman's visualization: https://twitter.com/JoshuaFeIdman/status/1176271562795868165 (https://twitter.com/JoshuaFeIdman/status/1176271562795868165) The geofacet package (https://cran.r-project.org/package=geofacet) is on CRAN! PB's geofacet: https://twitter.com/MYMRockMama/status/1178312979508391936 (https://twitter.com/MYMRockMama/status/1178312979508391936) Zhi Yang's geofacet: https://twitter.com/zhiiiyang/status/1176894911083212801 (https://twitter.com/zhiiiyang/status/1176894911083212801) Gil Henriques' geofacet: https://twitter.com/GilHenriques/status/1176909412503441408 (https://twitter.com/_Gil_Henriques/status/1176909412503441408) My animation: https://twitter.com/JonTheGeek/status/1178770430049558528 (https://twitter.com/JonTheGeek/status/1178770430049558528) Thomas Lin Pedersen on Twitter: @thomasp85 (https://twitter.com/thomasp85) The Question of the Week: https://rfordatascience.slack.com/archives/C6VCZPGPR/p1569686694114000 (https://rfordatascience.slack.com/archives/C6VCZPGPR/p1569686694114000) Check out the Tidyverse Dance (https://bit.ly/tidydance) and help SaveTheData! This week's data on Pizza Places: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-01 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-10-01)

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-17 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-17) Amit Levinson's visualization: https://twitter.com/Amit_Levinson/status/1174364639427272706 (https://twitter.com/Amit_Levinson/status/1174364639427272706) The ggimage package (https://cran.r-project.org/package=ggimage) is on CRAN! Scofirroto's remix animation: https://twitter.com/chucc900/status/1175059117188083712 (https://twitter.com/chucc900/status/1175059117188083712) Johanie Fournier's visualization: https://twitter.com/FournierJohanie/status/1174118994858651648 (https://twitter.com/FournierJohanie/status/1174118994858651648) Torsten Springer's visualization: https://twitter.com/spren9er/status/1175333672251265024 (https://twitter.com/spren9er/status/1175333672251265024) Otho Mantegazza's visualization: https://twitter.com/othomn/status/1175362011561168896 (https://twitter.com/othomn/status/1175362011561168896) The ggvoronoi package (https://cran.r-project.org/package=ggvoronoi) is on CRAN! The Question of the Week: https://rfordatascience.slack.com/archives/C8JP9ECBD/p1568079192043900 (https://rfordatascience.slack.com/archives/C8JP9ECBD/p1568079192043900) The tidymodels meta-package (https://cran.r-project.org/package=tidymodels) is on CRAN! Check out the Tidyverse Dance (https://bit.ly/tidydance) and help SaveTheData! This week's data on School Diversity: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-24 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-24)

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-10 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-10) Ariane Aumitre's visualization: https://twitter.com/ariamsita/status/1171421023838687232 (https://twitter.com/ariamsita/status/1171421023838687232) Liam Bailey's visualization: https://twitter.com/ldbailey255/status/1171538981818904577 (https://twitter.com/ldbailey255/status/1171538981818904577) Ryan Timpe's visualization: https://twitter.com/ryantimpe/status/1171578409836830720 (https://twitter.com/ryantimpe/status/1171578409836830720) Scofirroto's visualization: https://twitter.com/chucc900/status/1172772068422606850 (https://twitter.com/chucc900/status/1172772068422606850) This week's data on National Park Visits: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-17 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-17) The sf package: https://cran.r-project.org/web/packages/sf/index.html (https://cran.r-project.org/web/packages/sf/index.html) ggplot2::geom_sf: https://ggplot2.tidyverse.org/reference/ggsf.html (https://ggplot2.tidyverse.org/reference/ggsf.html)

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! For show notes and to subscribe see tidytuesday.com (https://www.tidytuesday.com) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-03 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-09-03) Gil Henrique's visualization: twitter.com/GilHenriques/status/1170008617526820864 (https://twitter.com/_Gil_Henriques/status/1170008617526820864) geom_smooth: ggplot2.tidyverse.org/reference/geom_smooth.html (https://ggplot2.tidyverse.org/reference/geom_smooth.html) My bar chart race: twitter.com/JonTheGeek/status/1170708866759364609 (https://twitter.com/JonTheGeek/status/1170708866759364609) Inspiration: www.reddit.com/r/dataisbeautiful/comments/cynql1/mooreslawgraphedvsrealcpusgpus19652019_oc/ (https://www.reddit.com/r/dataisbeautiful/comments/cynql1/moores_law_graphed_vs_real_cpus_gpus_1965_2019_oc/) Tutorial: towardsdatascience.com/create-animated-bar-charts-using-r-31d09e5841da (https://towardsdatascience.com/create-animated-bar-charts-using-r-31d09e5841da) gganimate (https://CRAN.R-project.org/package=gganimate) is available on CRAN! This week's data on amusement park injuries: twitter.com/thomas_mock/status/1171081818331930626 (https://twitter.com/thomas_mock/status/1171081818331930626) naif: dplyr.tidyverse.org/reference/na_if (https://dplyr.tidyverse.org/reference/na_if) casewhen: dplyr.tidyverse.org/reference/case_when (https://dplyr.tidyverse.org/reference/case_when)

Follow the show at @tidypod (https://twitter.com/tidypod) on Twitter! Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data: github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-08-27 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-08-27) Gil Henrique's visualization: twitter.com/GilHenriques/status/1166440262773567488 (https://twitter.com/_Gil_Henriques/status/1166440262773567488) Gina Reynolds' walk-through: twitter.com/EvaMaeRey/status/1167085280580558849 (https://twitter.com/EvaMaeRey/status/1167085280580558849) Check out happygitwithr.com (https://happygitwithr.com/) by @JennyBryan (https://twitter.com/jennybryan) Jake Kaupp's visualization: twitter.com/jakekaupp/status/1166874615286771717 (https://twitter.com/jakekaupp/status/1166874615286771717) tidygraph (https://CRAN.R-project.org/package=tidygraph) and ggraph (https://CRAN.R-project.org/package=ggraph) are available on CRAN! ggraph is now v2.0! twitter.com/thomasp85/status/1168542736833814528 (https://twitter.com/thomasp85/status/1168542736833814528) This week's data on Moore's law: twitter.com/thomas_mock/status/1168697769319653377 (https://twitter.com/thomas_mock/status/1168697769319653377)

Follow the show at @tidypod (https://twitter.com/tidypod) Join us at r4ds.online (http://r4ds.online) @R4DSCommunity (https://twitter.com/R4DSCommunity) Host: Jon Harmon @jonthegeek (https://twitter.com/jonthegeek) jonthegeek.com (http://jonthegeek.com/) Support us at patreon.com/tidytuesday (https://www.patreon.com/tidytuesday) Last week's data (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-08-20) | Our World in Data Blog (https://ourworldindata.org/nuclear-weapons) Cedric Scherer's visualization (https://twitter.com/CedScherer/status/1164611545294417922) #TidyTuesday (https://twitter.com/search?q=%23TidyTuesday) tidytuesday.rocks (https://nsgrantham.shinyapps.io/tidytuesdayrocks/) by Neal Grantham (https://twitter.com/nsgrantham) colorspace package (https://CRAN.R-project.org/package=colorspace) Claus's trick (https://github.com/clauswilke/practical_ggplot2/blob/6b0136c90609a5122cf239a84cc38415f00fb4ea/corruption_human_development.Rmd#L41-L46) Claus Wilke on Twitter (https://twitter.com/ClausWilke) This week's data (https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-08-27) | Wikipedia article (https://en.wikipedia.org/wiki/List_of_The_Simpsons_guest_stars) Andrew Collier (https://github.com/datawookie)

Roger and Hilary follow up on leaf umbrellas and take some time to discuss what's happening with R, the Tidyverse, and RStudio and how it's related to what's happening more broadly in the world of the Internet. Show notes: Support us through our Patreon page Leaf umbrella Roger on Twitter: https://twitter.com/rdpeng Hilary on Twitter: https://twitter.com/hspter Get the Not So Standard Deviations book: https://leanpub.com/conversationsondatascience/ Subscribe to the podcast on Apple Podcasts: https://itunes.apple.com/us/podcast/not-so-standard-deviations/id1040614570 Subscribe to the podcast on Google Play: https://play.google.com/music/listen?u=0#/ps/Izfnbx6tlruojkfrvhjfdj3nmna Find past episodes: http://nssdeviations.com Contact us at nssdeviations@gmail.com

Now that you know what R libraries and packages are, how do you go about finding good ones? Anders Larson, FSA, MAAA and Shea Parkes, FSA, MAAA, discuss some strategies for sifting through the massive number of packages available through CRAN or other sources. They also hone in on the Tidyverse, an ecosystem of useful packages for a wide range of tasks.

Hilary and Roger provide updates about coffee and oat milk, talk about the unbundling of the data scientist job, R style guides, quantifying the performance of music services, and KPI design. And the return of #hilaryshabits! Show notes: Google R Style Guide Henrik Bengtsson's style guide Tidyverse style guide Radical Change is Coming to Data Science Jobs Support us through our Patreon page Roger on Twitter: https://twitter.com/rdpeng Hilary on Twitter: https://twitter.com/hspter Get the Not So Standard Deviations book: https://leanpub.com/conversationsondatascience/ Subscribe to the podcast on Apple Podcasts: https://itunes.apple.com/us/podcast/not-so-standard-deviations/id1040614570 Subscribe to the podcast on Google Play: https://play.google.com/music/listen?u=0#/ps/Izfnbx6tlruojkfrvhjfdj3nmna Find past episodes: http://nssdeviations.com Contact us at nssdeviations@gmail.com

「RユーザのためのRStudio実践入門」執筆者と語る「宇宙(本)」のできるまで。担当ページの内容、書いている際に思っていたことなどを聞きました。 後編: 16. 「RユーザのためのRStudio実践入門」執筆者に聞く！パイプ演算子との付き合い方ほか RユーザのためのRStudio[実践]入門… 出版社のページ RユーザのためのRStudio［実践］入門 ―tidyverseによるモダンな分析フローの世界―… サポートページ。正誤表はこちら。 rstudiobook… サンプルコードはこちらから タイムテーブル 自己紹介 01:07 宇宙(本)の始まり 11:00 1章… 「RStusioを使うならプロジェクト機能を使いましょう」「執筆時点での最新機能は網羅しています」「あとで辞書的に見返せるように」 by y__mattu 15:15 2章… 「どのパッケージで何ができるのかを意識した」 by y__mattu 17:47 3章… 「死ぬ前に書き残しておこう」「(vignettes) 読めよ」「変わらないものを書こうと思った」 by yutannihilation 21:00 4章… 「エスカレータ式に理解していって、最後のページをめくる時に初心者を脱していられるように」「自分自身の備忘録も兼ねて盛り込んだ」 by kyn02666 26:02 5章… 「できるだけコンパクトに。新しいことよりも要約することを意識した」「書き足りないので薄い本を…」 by kazutan 27:30 関連リンク Rで欲しい県について国勢調査 小地域 Shapefile を全部ダウンロードする 「政府統計の総合窓口（e-Stat）」のリニューアル Tidyverseとは RStudio v1.1 Preview: Terminal RStudio IDE Custom Theme Support RStudioでDarkなテーマを当ててみる 初心者セッション 〜データハンドリング編〜 初心者セッション 1 データ読み込み編 Rによるスクレイピング入門 dplyrのselectとmutateのセマンティクスの違い tidyrのmulti-gatherの未来 Enhancing gather() and spread() by Using “Bundled” data.frames Kazutan.R 再現可能性のすゝめ―RStudioによるデータ解析とレポート作成― Announcing the 1st Bookdown Contest 著者陣のブログ y__mattu… RユーザのためのRStudio[実践]入門 という本が出ます。 yutannihilation… RユーザのためのRStudio[実践]入門 という本が出ます。 kazutan… RユーザのためのRStudio[実践]入門 という本が出ます。 kyn02666… RユーザのためのRStudio[実践]入門という本が出ます。

Hugo speaks with Renee Teate about the many paths to becoming a data scientist. Renee is a Data Scientist at higher ed analytics start-up HelioCampus, and creator and host of the Becoming a Data Scientist Podcast. In addition to discussing the many possible ways to become becoming a data scientist, they will discuss the common data scientist profiles and how to figure out which ones may be a fit for you. They’ll also dive into the fact that you need to figure out both where you are in terms of skills and knowledge and where you want to go in terms of your career. Renee has a bunch of great suggestions for aspiring data scientists and also flags several important pitfalls and warnings. On top of this, they'll dive into how much statistics, linear algebra and calculus you need to know in order to become an effective data scientist and/or data analyst. Links from the show FROM THE INTERVIEW Becoming a Data Scientist (Renée's Blog) Renée's Twitter Data Sci Guide (Data Science Learning Directory) FROM THE SEGMENTS Statistical Distributions and their Stories (with Justin Bois at ~19:20) Justin's Website at Caltech Probability distributions and their stories Programming Topic of the Week (with Emily Robinson at ~43:20) Categorical Data in the Tidyverse, a DataCamp Course taught by Emily Robinson. R for Data Science Book by Hadley Wickham (Factors Chapter) Inference for Categorical Data, a DataCamp Course taught by Andrew Bray. stringsAsFactors: An unauthorized biography (Roger Peng, July 24, 2015) Wrangling categorical data in R (Amelia McNamara & Nicholas J Horton, August 30, 2017) Original music and sounds by The Sticks.

アメリカで行われたRStudio主催のカンファレンスの振り返りとして、uriboとyutannihilationが情報交換を行いました。 ばしょ @Discord (つくば - とーきょー) 関連リンク rstudio::conf 2018 All things R & RStudio Tidyverse Twitter#RStudioConf RStudio公式の資料まとめリポジトリ rstudio::conf 2018 summary #rstudioconf - I shot a few pix when we were in San Diego so I put them on a shared Goog Pix album. Take what you want, leave some if you have pix to share. Tag friends. https://t.co/1ABqnnvn8f cc @dataandme @topepos @jaredlander @robinson_es @hugobowne @rstudio @hadleywickham— JD Long (@CMastication) February 11, 2018 Highlight of #rstudioconf. Being an official mic thrower. #blessed pic.twitter.com/ZetI3to5Bq— Tanya Cashorali (@tanyacash21) February 4, 2018 This was a nice installation. pic.twitter.com/T9SSttTHCh— Romain François (@romain_francois) February 1, 2018

Werner Schuster talks to Martin Hadley, data scientist at University of Oxford. They discuss the state of the R language, the rich R ecosystem that covers development (RStudio), notebooks for publication (R Notebooks, RPubs), writing web apps (Shiny), and the pros/cons of the different data frames implementations. Why listen to this podcast: - R is the tool for working with rectangular data - Modern data frame implementations are Tibble and data.table (for large amounts of data) - RMarkdown and R Notebooks allow to explore data and then publish it the results and (interactive) visualization - Use Shinyapps to publish server side R applications - Tidyverse is the place to look for modern R packages More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2twOXWJ You can also subscribe to the InfoQ newsletter to receive weekly updates on the hotest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Want to see extented shownotes? Check the landing page on InfoQ: http://bit.ly/2twOXWJ

In this episode: Hefin Rhys, Author of Machine Learning with R, the tidyverse, and mlrLearn more about your ad-choices at www.humainpodcast.com/advertiseYou can support the HumAIn podcast and receive subscriber-only content at http://humainpodcast.com/newsletter.