Graphics in R

Graphics in R base and ggplot2 Workshop:

From Basics to Brilliance



I’m sure you’ve heard that one of R’s big advantages are its amazing graphics capabilities.

But R can be a bit…intimidating.

The downside of being able to create graphs exactly how you want them is you have to know how to get R to do exactly what you want.

In this nine hour workshop, you will learn just that.

We’ll start with drawing very basic univariate and bivariate graphs using R’s defaults and the graphics that come with Base R: scatter plots, bar charts, histograms, dot charts, pie charts and other types of graph.

Then we’ll go beyond defaults–how to customize even these basic graphs in many cool ways.

We could stop there, and you’d already have an amazing graphics toolbox.

But of course, to really capture R’s potential, you need to go beyond basics. So we’re going to explore, in detail, a very powerful package: ggplot2.

We will cover the topics at a relaxed pace, and you will have many opportunities to ask questions.

The example data sets are taken from education and the physical and biological sciences, but the ideas and syntax are applicable for creating graphs for every discipline, including business, the bio-medical sciences, psychology and the social sciences.

After taking this workshop, you will be able to create beautiful graphs for your own research or analysis.

In this Workshop, you will learn:

Part 1: Base Graphics in R, one step at a time

  • Basic graphics techniques and syntax
  • Creating scatter plots and line plots
  • Customizing axes, colors, and symbols
  • Adding text: legends, titles and axis labels
  • Adding interpolation lines, regression lines and curves
  • Saving your plots to multiple formats: pdf, postscript, jpg
  • Increasing complexity: graphing multiple variables, multiple graphs and multiple axes
  • Including mathematical expressions on your graphs
  • Labelling points with text
  • Making graphs clear and pretty: including a grid, point labels, and shading
  • Shading and coloring your graph

Part 2: More techniques using Base Graphics in R

  • Setting symbol color size and shape to data
  • Mapping symbol color, size and shape to categorical data
  • Creating facet plots
  • Creating multiple curves on your graph
  • Creating bar charts, histograms, box plots, pie charts and dot charts
  • Adding smoothers to your graph
  • Creating scatterplot matrices
  • Creating functions for plotting
  • Including error bars easily

Part 3: Loading and using the qplot package

  • Loading the ggplot2 package
  • Using basic qplot graphics techniques and syntax to customize in easy steps
  • Creating scatterplots and line graphs
  • Mapping symbol or line size, type and color to categorical data
  • Including regressions and confidence intervals on your graph
  • Shading and coloring your graph
  • Creating bar charts, histograms, box plots, pie charts and dot charts
  • Labelling points on your graph

Part 4: Creating professional-levels graphs using qplot 

  • Creating histograms and density plots
  • Creating simple, stacked and grouped bar charts
  • Creating scatterplots and line graphs
  • Creating box plots
  • Including dates  on your graph
  • Shading and coloring your graph

Part 5: Getting started with ggplot2

  • Creating scatter graphs
  • Adding axis labels and titles
  • Controlling backgrounds, sizes, transparencies and colors
  • Mapping symbol and line size, type and color to categorical data
  • Controlling symbol shapes and using pretty color schemes
  • Modifying the axes
  • Using ggplot’s color palettes

Part 6: More customizations with ggplot2

  • Creating histograms, bar charts and box plots
  • Labelling points on your graph
  • Including regression lines and other smoothers



But can I keep up?

The workshop is pitched at a level that should make it of interest to both students and professionals.

You need some prior experience in R if you want to be able to use what you’ve learned. However, the material should be accessible to those somewhat new to R.

You do need to spend some time each week. You will learn concepts and get some clarity if you don’t practice what you’ve learned on your own. But you won’t entirely get it.

This is a workshop where you want to get your hands dirty with some data. Please expect to spend 2-3 hours per module just revising the hand-outs and doing the exercises.

This workshop is for you if you:

  • Want to learn how to create amazing graphs in R.
  • Have been using R, but would like to develop your R skills.
  • Have the time to really invest in learning. It will require about 4-6 hours per module all together.

It is not for you if you:

  • Are a complete beginner in statistics.
  • Have never seen R before.
  • Have no time to practice what you’ve learned.


  • You will get the most out of the workshop if you have had at a minimum of one statistics class.
  • You will need to have R installed on your computer.
  • You should have some experience with R. You should have at least a basic understanding of how R handles objects, data, and how to input commands and read output.

The workshop is offered as an interactive, live online workshop + Membership Site

Attend the workshop live via webinar. You will hear the instructor and see exactly what is happening on his screen. Ask questions through phone, microphone, or chat.

During the webinar sessions, the instructor will present concepts and explain the meaning of the techniques in that module, demonstrate how to implement those techniques in R on different examples, and answer your questions.

You also get video screenshot recordings of each workshop session made available within 48 hours. So you can review the material right away, a year later, or while doing the exercises. Or if you need to miss one (or all!) of the live sessions, you can still participate on your own schedule.

You will also get a membership to the workshop site. The site is our home base for the workshop. It’s where you’ll find everything you need to support your learning of each module:

Text data files. These are real data files from real research projects. You get full access to use the data to try everything on your own.

Handouts with all the R code to run and explore all of the examples yourself. You won’t learn it unless you try it. So you’ll get my code so you can follow along.

Exercises. (Yes, homework!). You really need to practice this stuff. Get your hands dirty. So we’re giving you the data to try it on your own with new models to try out. But don’t worry–you won’t be on your own stuck on some coding error that won’t work. You’ll get the code to do the exercises and the answers in case you get stuck.

But best of all, you can submit questions. So if there’s something you thought was clear during the workshop, but isn’t now that you’re reviewing the explanatory material, just type in your question. David will answer quick questions right there on the website.

Bonus videos from some webinars on relevant topics to help jog your memory or clear up misunderstandings. Included are:

– Ten Data Analysis Tips in R
– 13 Steps to Running Any Statistical Model

You’ll have access for a year to this workshop membership site. So as we add resources, re-record sessions, and answer more questions each time we offer the workshop, you have access to the updated material.

The Instructor:


David Lillis

David Lillis has taught R to many researchers and statisticians.

His company, Sigma Statistics and Research Limited, provides both on-line instruction and face-to-face workshops on R, and coding services in R.

David holds a doctorate in applied statistics and is a frequent contributor to The Analysis Factor, including our blog series R is Not So Hard.

What Our Students Say About David’s Workshops:


“David was clear, knowledgeable, and responsive. Great handouts!”

– Anonymous

“For me, it was a good introduction to R, using simpler (well understood) statistical techniques that did not detract from the introduction to R.”

– Martin Watts, PhD

It was great to see someone using R ‘live’ to see how it works.

– Cate Bailey

The explanation was very clear, the topics were useful.

– Jose Hernandez

“Great format, great presenter.”

– Tom Bohon

“I am a new R user; It just gave me another motivation why I need to learn it further. Great work.”

– Essam Alshreafi

“Learned more efficient ways to parse data and evaluate the contents of a given data set. Very nice stuff! Overall, I thought this webinar was very well done. It was informative and moved at a great pace.”

– anon

“More on R from David would be great. His tips were wonderful.”

– Gary Kitchen

Thanks for this, thought it was great and what a magnificent way to teach people stuff… keep up the good work!

– Joop van Eerbeek

“It was a very thorough set of workshops, a good pace, and it should prove to be an asset to my future data analysis projects (assuming that I dedicate some time to reviewing the concepts presented in the series).”

– David Scott

“I would recommend this course because it provides a proper introduction to R, paving the way for a self directed learning in R.”

– Mohammed Ahmed

The Details:

The live workshop sessions will be Thursdays 11:30am-1pm U.S. Eastern Time (GMT -5) on:

Jan 22
Jan 29
Feb 5
Feb 12
Feb 19
Feb 26

The live Question & Answer sessions will be 12-1pm U.S. Eastern Time (GMT -5) on:

Jan 28
Feb 11
Feb 25
Mar 13


Full Workshop Investment: $347

Sorry, this workshop is full, and registration has closed.

To get first notice when it opens again, please join our Mailing List. Check out some of our other online workshops too!

Refund Policy: Your registration fee is fully refundable up to 72 hours in advance. Because enrollment is limited, no refunds will be granted after the program begins.


As with all our programs, your satisfaction is guaranteed. If you participate fully in this workshop–watch, read, and try out everything included–and find you are not satisfied for any reason, we will give you a full refund, no questions asked.

Just notify us within 90 days of purchasing the program.