Preface
About PDV
Funding Acknowledgement
Datasets
Dedication
Contents
Contributors
1
Overview
1.1
Historical Perspective
1.2
Infographics vs. Visualizations
1.3
Principles of Analytical Design
1.3.1
Comparisons
1.3.2
Causality, Mechanism, Structure, Explanation
1.3.3
Multivariate Analysis
1.3.4
Integration of Evidence
1.3.5
Documentation
1.3.6
Content First and Foremost
1.4
Dashboard Basics
1.4.1
Dashboard Fundamentals
1.4.2
Dashboard Structure
1.4.3
Dashboard Design
1.4.4
Examples
2
Basics of Data Visualization
2.1
Data Exploration
2.1.1
Pre-Analysis Uses
2.1.2
Data Exploration in Action: the Algae Bloom Dataset
2.2
Workhorse Data Visualizations
2.2.1
Rug Plots
2.2.2
Bar Charts and Histograms
2.2.3
Line Charts
2.2.4
Scatterplots
2.3
Representing Multivariate Observations
2.4
Communicating Analysis Results
2.5
Hall-of-Fame / Hall-of-Shame
2.5.1
Misleading Charts
2.5.2
Home Runs
2.5.3
Strike-Outs
3
Essentials of Visual Design
3.1
The Mechanics of Visual Perception
3.1.1
Background
3.1.2
Gestalt Principles
3.1.3
Data Viz and Gestalt Guidelines
3.1.4
Examples
3.2
Visual Design and Data Charts
3.2.1
Visualization and Memory
3.2.2
Colour, Sizing, and Layout Considerations
3.2.3
Decluttering
3.2.4
The Layered Grammar of Graphics
3.2.5
Examples
3.3
Accessibility Considerations
3.3.1
Sonifications and Physicalizations
3.3.2
Colourblindness
3.3.3
General Resources
3.3.4
Practical Suggestions
4
Visualization and Storytelling
4.1
Stories and Storytelling
4.1.1
What Are Stories?
4.1.2
Elements of Storytelling
4.1.3
Form and Structure
4.1.4
How to Tell a Story
4.2
Effective Storytelling Visuals
4.2.1
Stories and Illustrations
4.2.2
Data and Stories
4.2.3
Evolving a Storytelling Chart
4.2.4
Anatomy of Storytelling Dashboards
5
Practical Aspects of Data Visualization
5.1
Visualization Toolkit
5.1.1
Simple Text and Tables
5.1.2
Scatterplots and Bubble Charts
5.1.3
Linegraphs and Sparklines
5.1.4
Bar Charts and Histograms
5.1.5
Area Charts and Treemaps
5.1.6
Boxplots
5.1.7
Maps, Heat Maps, and Choropleths
5.1.8
Parallel Coordinates
5.1.9
Text Visualizations and Representations
5.1.10
Trees, Dendrograms, and Network Diagrams
5.1.11
Small Multiples
5.1.12
Interactive and Animated Visualizations
5.1.13
Miscellaneous Charts
5.2
Visualization Software
5.2.1
GUI Tools
5.2.2
Command Line Tools
5.2.3
Integrated Tools
5.3
Getting Started With Power BI
5.3.1
Power BI Set-Up
5.3.2
Importing and Modeling Data
5.3.3
Calculations and Charts
5.3.4
Organizing Data
5.3.5
Data Wrangling
5.4
Power BI Beyond the Basics
5.4.1
Importing Data
5.4.2
Data Wrangling
5.4.3
Data Modeling
5.4.4
Best Practices
5.4.5
Doing More With DAX
5.5
Basic Visualizations in
R
5.5.1
Scatterplots
5.5.2
Barplots
5.5.3
Histograms
5.5.4
Curves
5.5.5
Boxplots
5.5.6
Examples
5.6
ggplot2
Visualizations in
R
5.6.1
Basics of
ggplot2
’s Grammar
5.6.2
ggplot2
Miscellenea
5.6.3
Examples
6
Exercises
References
Published with bookdown
The Practice of Data Visualization
5.4
Power BI Beyond the Basics
5.4.1
Importing Data
Pulling Data From Folders
PDF and Web Scraping
5.4.2
Data Wrangling
Merging Tables
Pivoting Data
Parameters
5.4.3
Data Modeling
Cross Filter Direction
Cardinality
Data Model Types
5.4.4
Best Practices
Declaring Variables
Boolean Logic
5.4.5
Doing More With DAX
Calculated Tables
Nested IF
Ranking
Filtering
GoC Fiscal Years
Advanced Formatting
What-If Parameters