The R-Podcast

Giving practical advice on how to use R for powerful and innovative data analyses.

The R-Podcast Episode 16: Interview with Dean Attali

Direct from the first-ever Shiny Developer conference, here is episode 16 of the R-Podcast! In this episode I sit down with Dean Attali for an engaging conversation about his journey to using R, his motivation for creating the innovative shinyjs package, and his perspective on teaching others about R through his support of the innovative and highly-praised Stats 545 course at UBC. In addition you'll hear about how his previous work prepared him well for using R, his collaboration with the RStudio team, and much more. I hope you enjoy this episode and thanks for listening!

Direct Download: [mp3 format] [ogg format]

Episode 16 Show Notes

Dean Attali (@daattali)

Package Pick

Feedback

  • Leave a comment on this episode's post
  • Email the show: thercast[at]gmail.com
  • Use the R-Podcast contact page
  • Leave a voicemail at +1-269-849-9780

Music Credits

The R-Podcast Episode 15: Introduction to Shiny

Just in time for the new year is a new episode of the R-Podcast! I give a brief introduction to the Shiny package for creating web applications using R code, provide some of my tips and tricks I have learned (sometimes the hard way) when creating applications, and point to excellent resources and example apps in the community that show the immense potential at your fingertips. You will see that r-podcast.org has gotten a major overhaul, and as a consequence the RSS feeds have changed slightly. Be sure to check out the Subscribe page for the updated feeds, but all of the previous episodes have been migrated successfully. As always you can provide your feedback in multiple ways:

  • New Feature: Provide a comment on this episode post directly (powered by the Disqus commenting system)
  • Email the show at thercast[at]gmail.com
  • Use the new Contact Form directly on the site.
  • Leave a voicemail at at +1-269-849-9780

Happy New Year and I hope you enjoy the episode!

Direct Download: [mp3 format] [ogg format]

Episode 15 Show Notes

r-podcast.org gets a face lift!

  • Now powered by the awesome Nikola static site generator. Able to write all content using markdown!
  • Potential to use R-Markdown for future content! See Edward Borasky's excellent tutorial: http://www.znmeb.mobi/stories/blogging-with-rstudio-and-nikola
  • Shout out to Roberto and the rest of the Nikola contributors for helping me fix some key migration issues! Still a few tweaks to go, pardon the dust as I continue to make improvements.
  • Now with SSL support via the lets encrypt initiative, and the certificate is absolutely free!

My shiny development tips

  • Start with the excellent Shiny development portal by RStudio as well as recent webinars
  • Also check Dean Attali's great tutorial on his blog
  • Shiny UI: Make sure to not have any missing commas or too many commas!
  • On top of the official shiny app gallery, also check out the shiny user showcase as well as showmeshiny.com for great examples.
  • Many shiny functions (such as reactive) allow you to supply R code enclosed in {} as the first parameter. Like writing a regular R function, make sure that you explicitely call the desired result object at the end or use a return call.
  • Using the sidebar layout is good for apps with a few UI controls and output containers, but my complex apps benefit from the flexibility offered by the grid layout system. See the layout article for more details.

Apps that helped me learn the power of Shiny

Keeping up with the Shiny community

New features to watch

R Community Roundup

Building Widgets blog by Kent Russell: Great showcase of converting many different javascript libraries for use in R, many of which are a great fit for Shiny.

Package Pick

News

ggplot2 version 2.0.0 released!
  • "Perhaps the bigggest news in this release is that ggplot2 now has an official extension mechanism. This means that others can now easily create their on stats, geoms and positions, and provide them in other packages. This should allow the ggplot2 community to flourish, even as less development work happens in ggplot2 itself. See vignette("extending-ggplot2") for details.
  • Additional details can be seen in the release notes

Feedback

  • Leave a comment on this episode's post
  • Email the show: thercast[at]gmail.com
  • Use the R-Podcast contact page
  • Leave a voicemail at +1-269-849-9780

Music Credits

The R-Podcast Episode 14: Tips and Tricks for using R-Markdown

The R-Podcast is back up and running! In this episode I discuss some useful resources and helpful tips/extensions that have greatly enhanced my work flow in creating reproducible analysis documents via R-Markdown. I also highlight some exciting new endeavors in the R community as well as provide my take on two key events that further illustrate the rapidly growing use of R across many industries. A big thank you to all who expressed their support during the extended hiatus, and please don't hesitate to provide your feedback and suggestions for future episodes. I hope you enjoy this episode!

Direct Download: [mp3 format] [ogg format]

Episode 14 Show Notes

Resources produced by RStudio:

Viewing R-Markdown output in real-time
  • Use Yihui's servr package to provide real-time viewing of document in RStudio viewer while editing the source file.
Creating tables in R-markdown:
  • Pander package offers many customized table options for markdown
  • kable function in the knitr package
Dealing with multiple output formats:

Insert following code chunk in beginning of document

{r, echo = FALSE} out_type <- knitr::opts_knit$get("rmarkdown.pandoc.to")

Then use conditional logic to perform different tasks depending on output type (docx, html, pdf, md)

Interactivity with R Markdown:

R Community Roundup

  • The R-Talk Podcast: Check out their interviews with David Smith and Jenny Bryan
  • Not So Standard Deviations Podcast: While not specifically focused on R, it has come up quite a bit in their early episodes, such as their talk of the impact of the "Hadleyverse"
  • METACRAN: METACRAN is a (somewhat integrated) collection of small services around the CRAN repository of R packages. It contains this website, a mirror at GitHub, a database with API, package search, database of package downloads (from the RStudio mirror), tools to check R packages on GitHub, etc.
  • Hadley Wickham's recent Redditt AMA!
  • First-ever Shiny Developer Conference to be held at Stanford University on January 30-21, 2016 (agenda)

Package Pick

  • captioner: An R package for generating figure/table numbers and captions, especially for Rmd docs
  • Using captioner vignette

News

Linux Foundation Announces R Consortium to Support Millions of Users Around the World
  • "The R language is used by statisticians, analysts and data scientists to unlock value from data. It is a free and open source programming language for statistical computing and provides an interactive environment for data analysis, modeling and visualization. The R Consortium will complement the work of the R Foundation, a nonprofit organization based in Austria that maintains the language. The R Consortium will focus on user outreach and other projects designed to assist the R user and developer communities."

  • "Founding companies and organizations of the R Consortium include The R Foundation, Platinum members Microsoft and RStudio; Gold member TIBCO Software Inc.; and Silver members Alteryx, Google, HP, Mango Solutions, Ketchum Trading and Oracle."

  • Hadley Wickham elected as chair of the Infrastructure Steering Committee (ISC)

  • "The R Consortium’s first grant is awarded to Gábor Csárdi, Ph.D., to implement R-Hub, a new service for developing, building, testing and validating R packages. R-Hub will be complementary to both CRAN, the major repository for open source R packages, and R-Forge, the platform supporting R package developers. R-Hub will provide build services, continuous integration for R packages and a distribution mechanism for R package sources and binaries."

Microsoft Closes Acquisition of Revolution Analytics
  • "R is the world’s most popular programming language for statistical computing and predictive analytics, used by more than 2 million people worldwide. Revolution has made R enterprise-ready with speed and scalability for the largest data warehouses and Hadoop systems. For example, by leveraging Intel’s Math Kernel Library (MKL), the freely available Revolution R Open executes a typical R benchmark 2.5 times faster than the standard R distribution and some functions, such as linear regression, run up to 20 times faster. With its unique parallel external memory algorithms, Revolution R Enterprise is able to deliver speeds 42 times faster than competing technology from SAS."

  • "We’re excited the work we’ve done with Revolution R will come to a wider audience through Microsoft. Our combined teams will be able to help more users use advanced analytics within Microsoft data platform solutions, both on-premises and in the cloud with Microsoft Azure. And just as importantly, the big-company resources of Microsoft will allow us to invest even more in the R Project and the Revolution R products. We will continue to sponsor local R user groups and R events, and expand our support for community initiatives. We’ll also have more resources behind our open-source R projects including RHadoop, DeployR and the Reproducible R Toolkit. And of course, we’ll be able to add further enhancements to Revolution R and bring R capabilities to the Microsoft suite of products."

The R-Podcast Episode 13: Interview with Yihui Xie

It's an episode of firsts on the R-Podcast! In this episode recorded on location I had the honor and privilege of interviewing Yihui Xie, author of many innovative packages such as knitr and animation. Some of the topics we discussed include:

  • Yihui's motivation for creating knitr and some key new features
  • How markdown plays a key role in making reproducible research more accessible
  • An innovative approach for publishing and maintaining reproducible statistical results online

And much more on this “lucky” episode 13 of the R-Podcast!

Direct Download: [mp3 format] [ogg format]

Episode 13 Show Notes

Resources mentioned during interview with Yihui
R Community Roundup
Package pick
  • Pandoc: Powerful and customizable document conversion
How to interact with the show
  • Submit your questions and comments via the R-Podcast contact page, or send an email to theRcast(at)gmail.com
  • Send in an audio comment via audio attachment to theRcast(at)gmail.com, or leave a voicemail on the R-Podcast voicemail hotline: +1-269-849-9780
  • Get show updates via our Twitter account: @theRcast
  • Follow us on our R-Podcast Google Plus page: gplus.to/thercast
  • Provide your favorite R community links at the R-Podcast subreddit: links.r-podcast.org/
Music Credits

Test from knitr to wordpress

Title

This is an R Markdown document. Markdown is a simple formatting syntax for authoring web pages (click the MD toolbar button for help on Markdown).

When you click the Knit HTML button a web page will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)

##      speed           dist

##  Min.   : 4.0   Min.   :  2

##  1st Qu.:12.0   1st Qu.: 26

##  Median :15.0   Median : 36

##  Mean   :15.4   Mean   : 43

##  3rd Qu.:19.0   3rd Qu.: 56

##  Max.   :25.0   Max.   :120

You can also embed plots, for example:

plot(cars)

plot of chunk
unnamed-chunk-2