paid course

Data Visualization in R with ggvis

Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

4 hours
11 Videos
45 Exercises
39,768 Participants
3,700 XP

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Course Description

In our ggvis data visualization course, you will learn how to create static and interactive graphs to display distributions, relationships, model fits, and more.

The first part of the course will focus on how to think conceptually about data visualizations using the theory behind the grammar of graphics.

Next, you will dive into the syntax of the R graphics package ggvis. Step-by-step, you'll learn how to create clear R data visualizations with sliders, widgets and text fields, and you’ll become familiar with the ggvis layering scheme to create multi-layered graphs.

Once you complete this data visualization class, you will be able to create meaningful static and interactive graphs to display distributions, relationships, and more!

Learn to create interactive graphs to display distributions, relationships, model fits, and more using ggvis.

Course Outline

Introduction to the ggvis package and the grammar of graphics. Learn the philosophy that guides ggvis and discover a clear, logical way to think about data visualization.

Discover how to build statistical transformations with the ggvis compute functions, as well as how to visualize the results. Learn shortcuts for visualizing transformations, such as smoothed lines, binned counts, and model predictions.

Change the appearance of axes and legends in your plots, and use the ggvis scale system to zoom in and out, to change the color scheme, and to control how your plot maps data values to visual properties.

Examine each part of the grammar of graphics, and learn the ggvis syntax to make it easier to think about plots.

Practice creating graphs that can be controlled through sliders, text fields, and other widgets. You'll also practice building sophisticated, multi-layered graphs with the ggvis layering scheme.

1
The Grammar of Graphics
Free

Introduction to the ggvis package and the grammar of graphics. Learn the philosophy that guides ggvis and discover a clear, logical way to think about data visualization.
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Lines and Syntax

Examine each part of the grammar of graphics, and learn the ggvis syntax to make it easier to think about plots.
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Transformations

Discover how to build statistical transformations with the ggvis compute functions, as well as how to visualize the results. Learn shortcuts for visualizing transformations, such as smoothed lines, binned counts, and model predictions.
View Chapter Details Play Chapter Now
Interactivity and Layers

Practice creating graphs that can be controlled through sliders, text fields, and other widgets. You'll also practice building sophisticated, multi-layered graphs with the ggvis layering scheme.
View Chapter Details Play Chapter Now
Customizing Axes, Legends, and Scales

Change the appearance of axes and legends in your plots, and use the ggvis scale system to zoom in and out, to change the color scheme, and to control how your plot maps data values to visual properties.
View Chapter Details Play Chapter Now

Garrett Grolemund

Data Scientist at RStudio

Garrett is the author of Hands-On Programming with R and R for Data Science from O'Reilly Media. He is a Data Scientist at RStudio and holds a Ph.D. in Statistics, but specializes in teaching. He's taught people how to use R at over 50 government agencies, small businesses, and multi-billion dollar global companies; and he's designed RStudio's training materials for R, Shiny, dplyr and more and is a frequent contributor to the RStudio blog. He wrote the popular lubridate package for R.

Course Instructor

Garrett Grolemund

Data Scientist at RStudio

Collaborator(s)

Filip Schouwenaars

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Data Visualization in R with ggvis

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Course Description

Course Outline

The Grammar of Graphics

Section 1 - Introduction to ggvis

Load ggvis and start to explore

ggvis and its capabilities

Section 2 - The grammar of ggvis

ggvis grammar ~ graphics grammar

4 essential components of a graph

Transformations

Section 5 - Compute functions

Histograms (1)

Histograms (2)

Density plots

Shortcuts

Section 6 - ggvis and dplyr

ggvis and group_by

group_by() versus interaction()

Chaining is a virtue

Customizing Axes, Legends, and Scales

Section 9 - Axes and Legends

Axes

Legends

Legends (2)

Section 10 - Customize property mappings

Scale types

Adjust any visual property

Adjust any visual property (2)

"=" versus ":="

Interview with Winston Chang

Lines and Syntax

Section 3 - Three new types of syntax

Three operators: %>%, = and :=

Referring to different objects

Referring to different objects (2)

Properties for points

Section 4 - the line, a special type of mark

Properties for lines

Path marks and polygons

Display model fits

compute_smooth() to simplify model fits

Interactivity and Layers

Section 7 - Interactive plots

The basics of interactive plots

Input widgets in more detail

Input widgets in more detail (2)

Control parameters and values

Section 8 - Multi-layered plots

Multi-layered plots and their properties

Multi-layered plots and their properties (2)

There is no limit on the number of layers!

Taking local and global to the next level