#MakeoverMonday

Explore different perspectives and approaches to create more effective visualizations

#MakeoverMonday offers inspiration and a giant dose of perspective for those who communicate data. Originally a small project in the data visualization community, #MakeoverMonday features a weekly chart or graph and a dataset that community members reimagine in order to make it more effective. The results have been astounding; hundreds of people have contributed thousands of makeovers, perfectly illustrating the highly variable nature of data visualization. Different takes on the same data showed a wide variation of theme, focus, content, and design, with side-by-side comparisons throwing more- and less-effective techniques into sharp relief.

This book is an extension of that project, featuring a variety of makeovers that showcase various approaches to data communication and a focus on the analytical, design and storytelling skills that have been developed through #MakeoverMonday. Paging through the makeovers ignites immediate inspiration for your own work, provides insight into different perspectives, and highlights the techniques that truly make an impact.

• Explore the many approaches to visual data communication
• Think beyond the data and consider audience, stakeholders, and message
• Design your graphs to be intuitive and more communicative

• Assess the impact of layout, color, font, chart type, and other design choices

Creating visual representation of complex datasets is tricky. There’s the mandate to include all relevant data in a clean, readable format that best illustrates what the data is saying—but there is also the designer’s impetus to showcase a command of the complexity and create multidimensional visualizations that “look cool.” #MakeoverMonday shows you the many ways to walk the line between simple reporting and design artistry to create exactly the visualization the situation requires.

Foreword ix

Acknowledgments xi

About the Authors xv

Part I

Introduction 3

What Is Makeover Monday? 3

How Did Makeover Monday Start? 4

The Community Project 7

Pillars of Makeover Monday 16

How to Use this book 29

Part II

Chapter 1 Habits of a Good Data Analyst 33

Approaching Unfamiliar Data 33

Analysis versus Visualization 44

Take Your Time 47

Build Context Through Additional Research 48

Find Insights 50

Communicate Clearly 54

Ask Questions 57

Summary 61

Chapter 2 Data Quality and Accuracy 63

Working with Incomplete Data 64

Overcounting Data 74

Sense-Checking Data 76

Is the Data Aggregable? 80

Substantiating Claims with Data 88

Summary 90

Chapter 3 Know and Understand the Data 91

Using Appropriate Aggregations 92

Explaining Metrics 109

Identifying and Correcting Mistakes 115

Time Series Analysis 119

Summary 133

Chapter 4 Keep It Simple 135

What Is Simplicity? 135

Simplicity in Design 136

Simplicity in Analysis 150

Simplicity in Storytelling 153

Summary 157

Chapter 5 Attention to Detail 159

Typos 161

Punctuation 162

Formatting 162

Crediting Images and Data Sources 182

Summary 183

Chapter 6 Designing for the Audience 185

Creating an Effective Design 186

Designing for Mobile 196

Using Visual Cues for Additional Information 207

Using Icons and Shapes 208

Storytelling 211

Reviewing Your Work to Improve Its Quality 216

Summary 218

Chapter 7 Trying New Things 219

Developing a Sharing Culture 221

Summary 235

Chapter 8 Iterate to Improve 237

Why Iterate? 237

Examples of Effective Iteration 241

Giving and Receiving Feedback 256

Summary 263

Chapter 9 Effective Use of Color 265

The Significance of Color in Data Visualization 266

Using Color to Evoke Emotions 267

Using Color to Create Associations 273

Using Color to Highlight 281

Best Practices for Using Color 283

Using Background Colors 287

Using Text as a Color Legend 291

Summary 294

Chapter 10 Choosing the Right Chart Type 295

Area Charts 296

Stacked Bar Charts 299

Diverging Bar Charts 304

Filled Maps 309

Donut and Pie Charts 318

Packed Bubble Charts 325

Treemaps 331

Slopegraphs 338

Connected Scatterplots 345

Circular Histograms 353

Radial Bar Charts 360

Resources 366

Summary 366

Chapter 11 Effective Use of Text 367

Effective Titles and Subtitles 367

What Is Your Key Message? 377

Instructions and Explanations 386

Summary 398

Chapter 12 Using Context to Inform 399

The Importance of Context 400

Using Simple Metrics 402

Methods for Communicating Context 418

Summary 428

Part III

The Community 431

Long-Term Contributors 431

Educators 446

Employers 446

Organizations 447

Nonprofits 448

Social Impact 448

Makeover Monday Live Events 449

Makeover Monday Enterprise Edition 450

Source Lines 453

Index 457

ANDY KRIEBEL is Head Coach at The Information Lab Data School and a member of the Tableau Zen Master Hall of Fame. The Makeover Monday series originated from his blog at vizwiz.com, where he shares data visualization tips, tricks, and best practices.

EVA MURRAY is the Head of Business Intelligence at Exasol, a Tableau Ambassador, and a 2018 Tableau Zen Master. She has co-hosted Makeover Monday since 2017, and blogs about Tableau, travel, and triathlon at trimydata.com.

Praise for #MakeoverMonday

"We humans can't learn alone or only by studying rules and principles. We learn in collaboration — copying and getting feedback from others — and by practicing, to grasp how principles apply to the real world, and when it's appropriate to tweak them or even break them. This book, the product of the Makeover Monday collaborative initiative, exemplifies this understanding of how learning really works. If you've already read some classics in the literature about data visualization, the next step is to grab this book and peruse its many before-and-after examples. You'll love some, dislike others, and even loathe a few, but in the process of mulling over all them you'll become a better visualization designer." —Alberto Cairo, Knight Chair in Visual Journalism at the University of Miami, and author of The Truthful Art: Data, Charts, and Maps for Communication

"Visualizing data effectively is something you learn through practicing: making something, getting feedback, and iterating to refine and improve. The weekly #MakeoverMonday project has been a place for many people to do exactly that. With #MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time, Andy and Eva have curated the thousands of visuals they've seen into a guide packed with lessons, tips, anecdotes, and examples. If you work with data, you'll appreciate the varied and creative approaches, learn mistakes to avoid, and be inspired to do your own practicing to take your data visualization game to the next level!"
—Cole Nussbaumer Knaflic, author of storytelling with data

"#MakeoverMonday grew from a weekly blog series into a worldwide social data project, with some of the best talent in the data visualization community participating each week. This book compiles years of learning and hundreds of visualizations from that project into a practical guide that will prove essential for anyone working with data." —Jeffrey A. Shaffer, Co-author of The Big Book of Dashboards, Adjunct Professor teaching Data Visualization at the University of Cincinnati

"Real-word case studies? Captivating visualizations? Practical career tips? This book has it all. Phenomenal."
—Kirill Eremenko, CEO, SuperDataScience