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.  

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