RStudio is hosting two public workshops in San Francisco this December:
Dec. 03, 2012 - Effective data visualization with ggplot2
Dec. 04, 2012 - Reports and reproducible research
Course Instructor: Garrett Grolemund - RStudio Master Instructor
Save on registration fees by signing up for both now, or sign up for the one you want most. All participants for either workshop will receive a copy of all slides, exercises, data sets, and R scripts used in the course.
Discount pricing available for academics (33% off) and students (66% off). Space is limited, please contact us to confirm your eligibility.
What should I bring?
Monday - Effective data visualization
Dec. 03, 2012
Make beautiful, effective graphs using ggplot2 and the grammar of graphics.
Who should take this course?
You’ll get the most out of this class if you’ve already created a number of graphics with ggplot2 (particularly if you’ve only used
qplot). You should know how to get your data into R, and have performed at least a couple of successful data analyses.
In this course, you will learn how to make beautiful, effective graphs using ggplot2 and the grammar of graphics. We want to help you bring the plots living inside your head to life. To do this, we teach not only the technical skills of writing the code, but also how the human perceptual system works. The point of a visualization is to get data off the page and into your head. Therefore, it is important to understand the limitations of the human brain and how it will interpret the graphics you create.
- How to work with the human sensory system to create clear, effective graphics
- Customizing every aspect of a ggplot2 graph using layers, scales, coordinate systems, annotations, and themes
- Spotting and avoiding common mistakes in graph construction
What will you learn?
Through a series of lectures, demonstrations and hands-on exercises, you will learn to use ggplot2 to quickly build, polish, and customize R graphics. This course won’t just teach you how to make graphs, but also how to think critically about graph construction and communication. About half the class will be spent learning advanced ggplot2 skills. The other half will be spent learning about perception and practicing your skills by critiquing, recreating, and improving existing graphics.
Graphical perception - R and ggplot2 offer an extremely high level of customization. To make the most of this freedom - and to avoid misleading, confusing plots - you’ll need to understand what makes an effective graphic.
- Understand the strengths and weaknesses of the human sensory system
- Spot and avoid common graph construction problems
- Work with color to mitigate the effects of color blindness
- Critique and improve existing graphics
Grammar of graphics - Graphics resemble mathematics and computer programming because they are shaped by an underlying logic. If you understand this logic, you can write simple, efficient code for producing graphs.
- Use the basic structure of graphs to create thousands of types of plots
- Display complicated data in a clear fashion by layering components together
- Expand your ggplot2 vocabulary to encompass new geoms and statistical transformations
Polishing plots - All graphs must communicate an idea. You can help a graph communicate by purposefully adjusting the appearance of a plot.
- Control appearance of ggplot2 plots with a theming system
- Annotate plots with text, images, and even other plots
- Customize legends, axes, and labels
- Understand scales and coordinate systems
- Craft plots for maximum presentation impact
Tuesday - Reports and reproducible research
Dec. 04, 2012
Learn a workflow for generating polished, publishable, and reproducible presentations of R research.
Who should take this course?
To get the most out of this course, you should have done several data analyses in the past. You will need a basic working knowledge of R and writing R code.
This course will teach you a workflow for publishing polished and reproducible reports and presentations. Reproducibility is more than essential for good scientific research. It adds value to any data analysis and reproducible code works not only today, but tomorrow, next week, and next year. It saves you time and makes it easier to communicate and test your results.
- Advantages of reproducible research
- Best practices for interweaving text and code to directly generate PDF reports, HTML webpages, blog posts, and slideshows
- Different ways of sharing code and data such as github gists, R packages, and R scripts
- Tools and techniques to make your work reproducible
What will you learn?
Through a series of lectures and hands on activities, we will teach you how to do reproducible, time saving research. This includes best practices and how to easily publish reproducible reports, slides, and web presentations straight from R code. This ensures your research is easier to share, understand, test, and even recreate with new data.
Introduction to reproducible research - Reproducible research is essential for any organization or individual. It will more than pay for itself in the long run.
- How to save time (and money) by making research reproducible
- Best practices for reproducible research
- Approaches to combining code and text
Generating PDFs from R - Sharing your analysis couldn’t be easier with automated reports and polished presentations created from your R scripts.
- Generate PDF files from R code with RStudio
- Format documents with latex
- Embed code, equations, and findings into documents with
- Develop document templates to automate analysis and reporting
Create HTML documents from R - The web provides a convenient medium for sharing results with far away collaborators and the world moreover. We will teach you a streamlined workflow for publishing custom web reports and presentations straight from your R scripts.
- Generate HTML documents from R code with RStudio
- Write in markdown
- Publish HTML R documents online with RPubs
- Turn R code into HTML slides with slidify
- Easily publish R reports as blog posts
Sharing code and data - Collaboration is made easier if you know how to efficiently share code and data among team members. You’ll learn how to:
- Write code that communicates
- Choose between human readable and machine readable storage formats
- Avoid code rot by recreating exact coding conditions across R platforms
- Share code and data as packages, gists, and scripts
In certain cases, we may need to cancel this workshop due to circumstances beyond our control or otherwise. If this happens, RStudio will refund all registration fees for those who signed up. RStudio is not responsible for any related expenses incurred by registered attendees (including but not limited to travel and hotel expenses).
Until Nov 18, 2012 - Full refund, less 10% of registration fees
Nov 19, 2012 to Nov 25, 2012 - 50% refund of registration fees
Nov 26, 2012 and after - No refund available
All public workshops hosted by RStudio come with a no-questions-asked money-back guarantee.
When & Where
RStudio is a company dedicated to providing software, education, and services for the R statistical computing environment. We started RStudio because we were excited and inspired by R. To learn more about us, visit our website at www.rstudio.com.