You are currently browsing the category archive for the ‘Training’ category.

We’ve teamed up with DataCamp to make a self-paced online course that teaches ggvis, the newest data visualization package by Hadley Wickham and Winston Chang. The ggvis course pairs challenging exercises, interactive feedback, and “to the point” videos to let you learn ggvis in a guided way.

In the course, you will learn how to make and customize graphics with ggvis. You’ll learn the commands and syntax that ggvis uses to build graphics, and you’ll learn the theory that underlies ggvis. ggvis implements the grammar of graphics, a logical method for building graphs that is easy to use and to extend. Finally, since this is ggvis, you’ll learn to make interactive graphics with sliders and other user controls.

The first part of the tutorial is available for free, so you can start learning immediately.

RStudio has teamed up with O’Reilly media to create a new way to learn R!

The Introduction to Data Science with R video course is a comprehensive introduction to the R language. It’s ideal for non-programmers with no data science experience or for data scientists switching to R from Excel, SAS or other software.

Join RStudio Master Instructor Garrett Grolemund as he covers the three skill sets of data science: computer programming (with R), manipulating data sets (including loading, cleaning, and visualizing data), and modeling data with statistical methods. You’ll learn R’s syntax and grammar as well as how to load, save, and transform data, generate beautiful graphs, and fit statistical models to the data.

All of the techniques introduced in this video are motivated by real problems that involve real datasets. You’ll get plenty of hands-on experience with R (and not just hear about it!), and lots of help if you get stuck.

You’ll also learn how to use the ggplot2, reshape2, and dplyr packages.

The course contains over eight hours of instruction. You can access the first hour free from O’Reilly’s website. The course covers the same content as our two day Introduction to Data Science with R workshop, right down to the same exercises. But unlike our workshops, the videos are self-paced, which can help you learn R in a more relaxed way.

To learn more, visit Introduction to Data Science with R.

datacamp-dplyr

RStudio has teamed up with Datacamp to create a new, interactive way to learn dplyr. Dplyr is an R package that provides a fast, intuitive way to transform data sets with R. It introduces five functions, optimized in C++, that can handle ~90% of data manipulation tasks. These functions are lightning fast, which lets you accomplish more things—with more data—than you could otherwise. They are also designed to be intuitive and easy to learn, which makes R more user friendly. But this is just the beginning. Dplyr also automates groupwise operations in R, provides a standard syntax for accessing and manipulating database data with R, and much more.

In the course, you will learn how to use dplyr to

  • select() variables and filter() observations from your data in a targeted way
  • arrange() observations within your data set by value
  • derive new variables from your data with mutate()
  • create summary statistics with summarise()
  • perform groupwise operations with group_by()
  • use the dplyr syntax to access data stored in a database outside of R.

You will also practice using the tbl data structure and the new pipe operator in R, %>%.

The course is taught by Garrett Grolemund, RStudio’s Master Instructor, and is organized around Datacamp’s interactive interface. You will receive expert instruction in short, clear videos as you work through a series of progressive exercises. As you work, the Datacamp interface will provide immediate feedback and hints, alerting you when you do something wrong and rewarding you when you do something right. The course is designed to take about 4 hours and requires only a basic familiarity with R.

This is the first course in a RStudio datacamp track that will cover dplyr, ggvis, rmarkdown, and the RStudio IDE. To enroll, visit the datacamp dplyr portal.

Are you headed to Strata? It’s just around the corner!

We particularly hope to see you at R Day on October 15, where we will cover a raft of current topics that analysts and R users need to pay attention to. The R Day tutorials come from Hadley Wickham, Winston Chang, Garrett Grolemund, J.J. Allaire, and Yihui Xie who are all working on fascinating new ways to keep the R ecosystem apace of the challenges facing those who work with data.

If you plan to stay for the full Strata Conference+Hadoop World be sure to look us up in the Innovator Pavilion booth P14 during the Expo Hall hours. We’ll have the latest books from RStudio authors and “shiny” t-shirts to win. Share with us what you’re doing with RStudio and get your product and company questions answered by RStudio employees.

See you in New York City!

Registration is now open for the next Master R Development workshop led by Hadley Wickham, author of over 30 R packages and the Advanced R book. The workshop will be held on January 19 and 20th in the San Francisco bay area.

The workshop is a two day course on advanced R practices and package development. You’ll learn the three main paradigms of R programming: functional programming, object oriented programming and metaprogramming, as well as how to make R packages, the key to well-documented, well-tested and easily-distributed R code.

To learn more, or register visit rstudio-sfbay.eventbrite.com.

RStudio is planning a new Master R Developer Workshop to be taught by Hadley Wickham in the San Francisco Bay Area on January 19-20. This will be the same workshop that Hadley is teaching in September in New York City to a sold out audience.

If you did not get a chance to register for the NYC workshop but wished to, consider attending the January Bay Area workshop. We will open registration once we have planned out all of the event details. If you would like to be notified when registration opens, leave a contact address here.

The Joint Statistical Meetings (JSM) start this weekend! We wanted to let you know we’ll be there. Be sure to check out these sessions from RStudio and friends:

Sunday, August 3

  • 4:00 PM: A Web Application for Efficient Analysis of Peptide Libraries: Eric Hare*+ and Timo Sieber and Heike Hofmann
  • 4:00 PM: Gravicom: A Web-Based Tool for Community Detection in Networks: Andrea Kaplan*+ and Heike Hofmann and Daniel Nordman

Monday, August 4

  • 8:35 AM: Preparing Students for Big Data Using R and Rstudio: Randall Pruim
  • 8:55 AM: Thinking with Data in the Second Course: Nicholas J. Horton and Ben S. Baumer and Hadley Wickham
  • 8:55 AM: Doing Reproducible Research Unconsciously: Higher Standard, but Less Work: Yihui Xie
  • 10:30 AM: Interactive Web Application with Shiny: Bharat Bahadur
  • 2:00 PM: Interactive Web Application with Shiny: Bharat Bahadur

Tuesday, August 5

  • 2:00PM: Give Me an Old Computer, a Blank DVD, and an Internet Connection and I’ll Give You World-Class Analytics: Ty Henkaline

Wednesday, August 6

  • 10:35 Shiny: Easy Web Applications in R:Joseph Cheng
  • 11:00 AM: ggvis: Moving Toward a Grammar of Interactive Graphics: Hadley Wickham

For even more talks on R we thought Joseph Rickert’s “Data Scientists and R Users Guide to the JSM” was excellent. Click here to see it. http://blog.revolutionanalytics.com/2014/07/a-data-scientists-and-r-users-guide-to-the-jsm.html

While you’re at the conference, please come by our exhibition area (Booth #112) to say hello. J.J., Hadley and other members of the team will be there. We’ve got enough space to talk about your plans for R and how RStudio Server Pro and Shiny Server Pro can provide enterprise-ready support and scalability for your RStudio IDE and Shiny Server deployments.

We hope to see you there!

R Markdown is a framework for writing versatile, reproducible reports from R. With R Markdown, you write a simple plain text report and then render it to create polished output. You can:

  1. Transform your file into a pdf, html, or Microsoft Word document—even a slideshow—at the click of a button.
  2. Embed R code into your report. When you render the file, R will run the code and insert its results into your report. Use this feature to add graphs and tables to your report: if your data ever changes, you can update your figures by re-rendering the report.
  3. Make interactive documents and slideshows. Your report becomes interactive when you embed Shiny code.

We’ve created a cheat sheet to help you master R Markdown. Download your copy here. You can also learn more about R Markdown at rmarkdown.rstudio.com and Introduction to R Markdown.

RM-cheatsheet

We’ve added a new section of articles to the Shiny Development Center. These articles explain how to create interactive documents with Shiny and R Markdown.

You’ll learn how to

  • Use R Markdown to create reproducible, dynamic reports. R Markdown offers one of the most efficient workflows for writing up your R results.

  • Create interactive documents and slideshows by embedding Shiny elements into an R Markdown report. The Shiny + R Markdown combo does more than just enhance your reports; R Markdown provides one of the quickest ways to make light weight Shiny apps.

  • Take advantage of RStudio’s built in features that support R Markdown

interactive-articles.001

Learn more at shiny.rstudio.com/articles

The RStudio team recently rolled out new capabilities in RStudio, shiny, ggvis, dplyr, knitr, R Markdown, and packrat. The “Essential Tools for Data Science with R” free webinar series is the perfect place to learn more about the power of these R packages from the authors themselves.

Click to learn more and register for one or more webinar sessions. You must register for each separately. If you miss a live webinar or want to review them, recorded versions will be available to registrants within 30 days.

The Grammar and Graphics of Data Science
Live! Wednesday, July 30 at 11am Eastern Time US  Click to register

  • dplyr: a grammar of data manipulation – Hadley Wickham
  • ggvis: Interactive graphics in R – Winston Chang

Reproducible Reporting 
Live! Wednesday, August 13 at 11am Eastern Time US  Click to register

  • The Next Generation of R Markdown – Jeff Allen
  • Knitr Ninja – Yihui Xie
  • Packrat – A Dependency Management System for R – J.J. Allaire & Kevin Ushey

Interactive Reporting
Live! Wednesday, September 3 at 11am Eastern Time US  Click to register

  • Embedding Shiny Apps in R Markdown documents – Garrett Grolemund
  • Shiny: R made interactive – Joe Cheng

 

Follow

Get every new post delivered to your Inbox.

Join 12,254 other followers