Comprehensive Graphics Visualizations with R

Name: Comprehensive Graphics Visualizations with R
Rating: 4.1 (75 reviews)

Learn the important features of the base, ggplot and lattice ("trellis") graphical capabilities in R

Created byGeoffrey Hubona, Ph.D.

Last updated 9/2020

English

What you'll learn

Learn how to create a wide range of elegant and stunning graphical visualizations using the base, lattice and ggplot graphics systems in R.
Learn to use the R Commander interface to create a variety of 2D and 3D graphics using different data sets.
Learn to apply all of these graphical capabilities to your own data by practicing with all of the supplied course videos R scripts and by completiing each of the five sets of exercises - one for each section of the course.

Course content

5 sections • 69 lectures • 8h 31m total length

Introduction to Comprehensive Graphics with R !1:42
A Word on the Course and the Materials7:16
One Last Word: Installing R Console, RStudio, and R Commander5:16
Install the R console, RStudio, and R Commander, explore the materials zip, and complete course exercises while using the discussion board for questions.
Agenda and Graphics Architecture Overview9:17
Examine the graphics architecture in R Commander and R Studio, explore base graphics, lattice graphics, and G-G plie graphics, and learn to create interactive three-dimensional plots with mouse controls.
Plotting with R Commander (part 1)12:36
Plotting with R Commander (part 2)10:18
Plotting with R Commander (part 3)10:39
Scatterplot HH6:52
Explore scatterplot hh with the h.h. extension to plot by groups such as country, adjust point sizes, and inspect scatterplot matrix with least squares and smooth lines for multivariate relationships.
Scatterplot Matrix HH8:21
Plot of Means6:07
Strip Chart8:40
More Strip Chart7:43
3D Plots5:15

Exercise Solution and More on Base Graphics9:43
More Base Features Compared to ggplot8:17
Adding Text to Plots (part 1)8:45
Adding Text to Plots (part 2)9:31
Adding Shapes to Plots Interactively (part 1)7:22
Adding Shapes to Plots Interactively (part 2)7:39
Adding Shapes to Plots Interactively (part 3)8:05
Adding Nonlinear Fits to Plots (part 1)7:52
Adding Nonlinear Fits to Plots (part 2)6:10
Adding Nonlinear Fits to Plots (part 3)5:50
Adding Nonlinear Fits to Plots (part 4)5:26
Adding Nonlinear Fits to Plots (part 5)7:21
Learn to add nonlinear fits to plots in R using G-G plot and Q plot, visualize 95 percent confidence bounds, and adjust window span and data order for accurate lines.
Boxplots (part 1)5:55
Boxplots (part 2)7:25
Boxplots (part 3)7:23
Boxplots (part 4)10:21
Histograms6:54
Time Series and Piechart6:07
Create time series plots in base graphics to compare total, male, and female deaths by year, and illustrate pie chart labeling and interpretability.
Stripchart and Pairs Plot6:58

Day 3 Introduction, Exercise Solution, and Shingles7:02
Shingles, Coplot and Interaction Plots6:35
Interaction and XYplots6:25
Box and Whiskers Plot and Design Plot8:14
Effects Sizes5:34
Bubble and Sunflower Plots7:53
Begin Trellis Graphics with Histogram6:46
Density Plot6:31
Explore density plots in R using lattice graphics, grouping by score and adding autokey legends to display separate density curves for each group.
Begin Technical Overview of Lattice8:03
Update Oats Plot6:32
Update plots with the update function, adjust aspect ratio and layout for readability, add breaks with between, and use autokey with groups by year in the barley lattice plot.
Continue Dotplots6:29
More Densityplots7:26
QQMath Plots5:47
More Bwplots6:40
Compare distributions with q-q plots against theoretical and empirical distributions, revealing higher mean and lower variance for females in test scores, with box and whiskers and a box-cox transform.
Violin Plots7:37
Multiway Tables, More Barcharts and Dotplots7:10
Postdoc Barcharts4:57
More Dotplots8:17

Day 4 Introduction and Titanic Data (part 1)7:36
More Titanic Data and Charts9:02
More Elaborate XYPlots6:31
Continue Elaborate XYPlots Earthquake Data6:20
Continue Elaborate XYPlots Earthquake Data7:55
Explore elaborated xy plots of earthquake data in R, using depth breaks, color scales, legends, axis labeling, log scales, and smoothing with loess and local regression.
Elaborate XYPlot with Shingles7:42
Continue Elaborate XYPlots9:54
Update xy plots with panel functions and add right-hand scales for extra variables. Explore descriptive scatterplot matrices with grouped data and labeled axes from crime and car datasets.
Revisit ggplot2 (part 1)8:02
GGplot with Smooth Plots6:27
More GGplot Smooths7:54
More GGplot5:12
Different GGplots7:22
Still More GGplot Graphs and Charts8:53

Requirements

Students will need to install the R console software, RStudio and the R Commander R packages. They are each free and instructions are provided with the course materials.

Description

Comprehensive Graphics with R is a thorough, comprehensive overview of each of three major graphics approaches in R: base, lattice, and ggplot. The course also demonstrates the use of the R Commander interface to create a variety of 2D and 3D graphics. Most of the course is engaged in live, "hands-on" demonstrations of creating a wide range of 2D and 3D plots and graphs using extensive scripts and data sets, all provided with the course materials. Adequate documentation including slides, exercises and exercise solutions are also provided. The course demonstrates (and uses) two of the most popular ‘front-ends’ to the R Console: R Commander and RStudio. We begin by exploring the range of graphics output available using both the R Commander and RStudio GUI interfaces to the R Console. The course then follows with a more in-depth examination of the graphics capabilities for each of the three main graphics systems, base, lattice, and ggplot.

This course is a ‘must see’ for anyone who will use R and wishes to get the most out of the stunning variety of graphical charts, plots, and even animations that are available. The R software was designed from the outset to be particularly strong in visualization and graphical capabilities. However, if you are unaware of the full range of these capabilities you are missing opportunities to apply this wide variety of rich, powerful graphics to your own work and research projects. Accordingly, this course is specifically designed to comprehensively demonstrate and explain the broad range of graphical outputs that are available with R.

Who this course is for:

Anyone who uses R software for any reason will benefit from this course, including beginning, intermediate and advanced R users.
Anyone who wants to learn R will benefit from this course.
The course is especially appropriate for graduate students and faculty who wish to learn a graphics software alternative to SPSS or SAS, as well as working data analytics professionals and other quantitative professionals.

Comprehensive Graphics Visualizations with R

What you'll learn

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Course content

Orientation to Course and to R Graphics ("Pre-Session")13 lectures • 1hr 40min

DAY 1 Base Graphics Features compared to GGPlot6 lectures • 46min

DAY 2 Continue with Base Graphics versus Ggplot19 lectures • 2hr 23min

DAY 3 Begin Lattice ("Trellis") Graphics18 lectures • 2hr 4min

DAY 4 More Trellis Graphics and More GGplot Graphics13 lectures • 1hr 39min

Requirements

Description

Who this course is for: