Visualization in R with ggplot2

Visualization in R with ggplot2

taught by Randall Pruim

 
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Aim of Course:

In this online course, “Visualization in R with ggplot2,” participants will learn how to use the ggplot R Project to make, format, label and adjust graphs using R. 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.

NOTES:

(1) 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 customising plots.

(2) We acknowledge the contributions of Hadley Wickham, who pioneered this and other courses at Statistics.com.

This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

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 all that jazz
  • 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

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.

Visualization in R with ggplot2

Who Should Take This Course:
Statistical analysts who use R and need to create or modify graphs.
Level:
Intermediate
Prerequisite:
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. For this, we recommend you take R Programming - Introduction 1.
Organization of the Course:
Options for Credit and Recognition:
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.
Instructor(s):

Dates:

July 19, 2019 to August 16, 2019 January 10, 2020 to February 07, 2020 July 17, 2020 to August 14, 2020

Visualization in R with ggplot2

Instructor(s):

Dates:
July 19, 2019 to August 16, 2019 January 10, 2020 to February 07, 2020 July 17, 2020 to August 14, 2020

Course Fee: $549

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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