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Visualization in R with ggplot2

Visualization in R with ggplot2

This course will teach you ggplot as an implementation of the grammar of graphics in R. ggplot combines the advantages of base and lattice graphics while maintaining the ability to build up a plot step by step from multiple data sources.

Overview

In this course, participants will learn how to use the ggplot2 Project to make, format, label and adjust graphs using R. ggplot2 combines the advantages of base and lattice graphics while maintaining the ability to build up a plot step by step from multiple data sources. The ggplot2 Project, created by Hadley Wickham, is named after the term “Grammar of Graphics”, which was coined by Leland Wilkinson (creator of Systat) and won the 2006 John Chambers Award for Statistical Computing. This “grammar of graphics” is a system of describing and organizing the fundamental components of a graph and the process of creating a graph. Using ggplot2, participants will learn how to design and implement graphs in an efficient, elegant, and systematic manner, following principles of general good graphing practice.

NOTE: The course is available on a contract basis only. Have 6 or more people interested? Contact us for a group rate.

  • Intermediate
  • 4 Weeks
  • Expert Instructor
  • Tuiton-Back Guarantee
  • 100% Online
  • TA Support

Learning Outcomes

This course is ideal for statistical analysts who use R and need to create or modify graphs. In this online course, participants will learn how to use the ggplot2 Project to make, format, label, and adjust graphs using R.

 

  • Create basic plots (scatterplots, histograms, and barcharts)
  • Add extra variables with aesthetics (like color, shape, and size) or faceting
  • Display data in other forms (densityplots, boxplots, etc.) using geoms
  • Overcoming overplotting with drawing scatterplots of large datasets
  • Add group-wise summaries and transformations to your plots
  • Add labels, legends, and axes

Who Should Take This Course

Statistical analysts who use R and need to create or modify graphs.

Our Instructors

Dr. Randall Pruim

Dr. Randall Pruim

Randall Pruim is chair of Mathematics and Statistics department at Calvin College as well as director of the Calvin’s Integrated Science Research Institute (ISRI), which was founded in 2008 through a $1.1 million grant from the Howard Hughes Medical Institute. The ISRI organizes a number of initiatives to deepen integrated approaches to science research and education. Initiatives of the ISRI have led to grants from the NSF to provide scholarships to students who will combine computation with one of the traditional sciences like biology, chemistry, or physics and to renovate laboratory space to create the Integrated Science Research Lab, which combines both wet and in silico lab facilities in a state-of-the-art research space for faculty and students. Dr. Pruim is also part of Project MOSAIC, an NSF-funded initiative to improve the teaching of modeling, statistics, calculus, and computation nationally. The mosaic R package, available on CRAN, is a product of Project MOSAIC that makes it easier to teach calculus and statistics using R.

Course Syllabus

Week 1

Introduction to ggplot2

  • How to create basic plots (scatterplots, histograms, and barcharts) using qplot()
  • Setting vs. mapping
  • How to add extra variables with aesthetics (like color, shape, and size) or faceting

Week 2

Digging Deeper into ggplot2

  • The ggplot system: geoms, stats, and more
  • How to display data in other forms (densityplots, boxplots, etc.) using geoms
  • Techniques for overcoming overplotting with drawing scatterplots of large datasets

Week 3

Data Manipulation for Plotting, dplyr

  • Group-wise summaries and transformations to add extra information to your plots
  • How to visualize time series

Week 4

Polishing Your Plots

  • Tweaking your plots for maximum presentation impact
  • Introduction to color theory
  • Labels, legends, and axes
  • Using and adjusting the plot themes

Class Dates

1970

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Prerequisites

While ggplot2 is a mini-language specifically tailored for producing graphics, you will need some familiarity with data handling in R before taking this course.

Introduction to R Programming

This course provides an easy introduction to programming in R.
  • Skill: Intermediate
  • Credit Options: CAP, CEU
Karolis Urbonas
Susan Kamp
Stephen McAllister
Amir Aminimanizani
Elena Rose
Leonardo Nagata
Richard Jackson

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Visualization in R with ggplot2

Additional Information

Homework

Homework in this course consists of guided exercises in writing code for producing graphs.

In addition to assigned readings, this course also has discussion tasks, and supplemental readings available online.

Course Text

The instructor has prepared materials for use in the course. There is also a suggested text for review and reference –   ggplot2: Elegant Graphics for Data Analysis by Hadley Wickham.  The text may be purchased here.

Software

Participants should be familiar with and have access to R, and should download and install the ggplot2 Project before the course starts.

Supplemental Information

Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

 

Chrome

 

Firefox

 

Safari

  • Navidys (for colorblindness, dyslexia, and reading difficulties)
  • HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

Miscellaneous

On the two courses “R Graphics” and “Visualization in R with ggplot2:” Visualization in R with ggplot2 is more about the use of the ggplot2 package to easily produce high quality plots. R Graphics covers the the core R graphics functions and the lattice package for producing plots and also looks at lower-level tools for customizing plots. We acknowledge the contributions of Hadley Wickham, who pioneered this and other courses at Statistics.com.

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Visualization in R with ggplot2