The R-podcast

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!

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!

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!

This is not an April Fool's joke ... The R-Podcast is back once again! In this episode, I discuss the concept of version control and how you can get started with using the Git VCS right now with your R projects. Also I discuss a big batch of listener feedback, and highlight a couple of great visualization applications from the community using ggplot2. All of that and more on episode 12 of the R-Podcast!

Season 2 of the R-Podcast is up and running! This episode begins a multi-part series on reproducible analysis using R. In this episode I discuss the usage of Sweave and LaTeX for producing reproducible reports, an introduction to the capabilities of the knitr package (more episodes will be coming dedicated to this package), and my motivation for adapting reproducible analysis techniques and tools into my workflow. In our listener feedback segment I discuss a new means of providing feedback to the R-Podcast using our new sub-reddit page and introduce new segments highlighting interesting stories around the R community and useful packages. This promises to be an exciting season of the R-Podcast, and I hope you enjoy this episode!

I'm happy to present episode 10 of the R-Podcast! Season 1 of the R-Podcast concludes with part 2 of my series on data munging, in which I discuss issues surrounding importing data sets contained in HTML tables. I share how I used the XML and RCurl packages to validate and import data from hockey-reference.com for storage into a MySQL database. Our listener feedback segment contains another installment on the Pitfalls of R contributed by listener Frans. I want to thank everyone who has provided such positive feedback throughout the season, and I'm looking forward to providing some exciting new content for season 2. I hope you enjoy the episode and check out our new contact page if you would like to provide any feedback. Thanks for listening!

It’s great to be back with a new episode after an eventful break! This episode begins a series on my adventures in data munging, a.k.a data processing. I discuss three issues that demonstrate the flexibility and versatility R brings for recoding messy values, important inconsistent data files, and pinpointing problematic observations and variables. We also have an extended listener feedback segment with an audio installment of the “pitfalls” of R contributed by listener Frans. I hope you enjoy this episode and keep passing along your feedback to theRcast(at)gmail.com and stop by the forums as well!

I'm happy to present this jam-packed episode of the R-Podcast dedicated to using the ggplot2 package for visualization. This episode will have a companion screencast released in the next few days. I use data from the Hockey Summary Project to demonstrate how to create a series of boxplots of NHL regular season attendance for each team. The R code used in this episode will be available via GitHub. I also extend my thanks to the Going Linux podcast for plugging the R-Podcast.

Hello everybody, I am finally back with a new episode! In this episode: Hardware issues, major update to RStudio, new forums, and discussion on managing your workflow for projects. I discuss useful functions for executing R scripts and saving/loading R objects for future sessions, and summarize different solutions for organizing R code based on task and via the ProjectTemplate package, along with the importance of version control.

In this episode: Listener feedback and importing data from external sources into R. We dive into the basics of importing delimited text files using read.table and its varients. We also discuss recommendations for importing MS Excel spreadsheet files, relational databases such as MySQL, data from HTML tables, and files produced by other statistical computing packages.

After a brief delay here's episode 5 of the R-Podcast. In this episode: R 2.15.0 released, listener feedback, and discussion on basic package management. I discuss helpful resources for finding packages, installation procedures, and how to determine what packages are installed in your R system, among other considerations.

In this episode: Site updates, additional screencasts about R from other sites, listener feedback, and discussion on the fundamental data structures for R: vectors, matrices, lists, and data frames. The R code discussed in this episode is available in our GitHub repository, see the show notes for details.

In this episode: New versions of R and ggplot2 available, listener feedback, and an interactive session with R. The R code discussed in this episode will be available in our GitHub repository, see the show notes for details.

In this episode: A couple of site updates, our first listener feedback, an overview of installing R on each major platform, and an overview of R IDEs and helpful resources for getting started with R.

Here is the inaugural episode of the R-Podcast! In this episode, I take a few minutes to introduce myself and to explain the main goals of this podcast. I also define what R is and give an overview of R's history of development and features that distinguish it from other statistical software.