#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time

Description

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 communicationThink beyond the data and consider audience, stakeholders, and messageDesign your graphs to be intuitive and more communicativeAssess 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.   #MakeoverMonday Contents Foreword Acknowledgments From Andy and Eva From Andy From Eva About the Authors Andy Kriebel Eva Murray Part I Introduction What Is Makeover Monday? How Did Makeover Monday Start? The Community Project The Andys: Makeover Monday 2016 The Murray/Cotgreave Swap: Makeover Monday 2017 The Next Phase: Makeover Monday 2018 Pillars of Makeover Monday Developing Technical Skills Building a Data Visualization Portfolio Learning and Inspiration Networking Demonstrating Leadership Making an Impact How to Use this book Part II Chapter 1 Habits of a Good Data Analyst Approaching Unfamiliar Data Identify the Challenges Gain Insights from Metadata Explore the Data Analysis versus Visualization Take Your Time Build Context Through Additional Research Read the Available Information Seek Additional Information Find Insights Educating Your Audience Communicate Clearly Ask Questions Summary Chapter 2 Data Quality and Accuracy Working with Incomplete Data Incomplete Data Missing Data Excluding Data Tips for Working with Incomplete or Missing Data Overcounting Data Sense-Checking Data Trump’s Tweets Is Puerto Rico a State? Is the Data Aggregable? Adult Obesity in the United States Averages of Averages Substantiating Claims with Data Summary Chapter 3 Know and Understand the Data Using Appropriate Aggregations Can the Data Be Aggregated? Basic Aggregation Types Explaining Metrics Know Your Audience Using Appropriate Metrics Creating New Metrics to Tell a Different Story Identifying and Correcting Mistakes Time Series Analysis Univariate Time Series Visualizing Seasonality Using Moving Averages for Smoothing Variance from a Point in Time Cycle Plots Calendar Heat Map Summary Chapter 4 Keep It Simple What Is Simplicity? Simplicity in Design Simplicity in Layout and Positioning Simplicity in Colors and Icons Simplicity in Analysis Getting Started with New Data Start Simple Know When to Stop Simplicity in Storytelling Finding Insights Focusing on a Key Message Summary Chapter 5 Attention to Detail Typos Punctuation Formatting Formatting Charts Effectively Universal Formatting Crediting Images and Data Sources Summary Chapter 6 Designing for the Audience Creating an Effective Design What Is the Purpose? Who Is the Audience? Sketching Planning the Layout Designing for Mobile Know Your Audience Information Displays Color Choices Use of White Space Keep It Simple Bringing It All Together Using Visual Cues for Additional Information Using Icons and Shapes Proper Attributions Go Easy on the Shapes Storytelling Finding a Story and Sticking to It Long-Form Storytelling Think Like a Data Journalist Reviewing Your Work to Improve Its Quality Take a Step Back Ask a Friend Viz Review Summary Chapter 7 Trying New Things Developing a Sharing Culture Circular Charts Images from Dot Plots Patterns and Shapes Waffle Charts Tile Maps Borders and Lines Summary Chapter 8 Iterate to Improve Why Iterate? Agile Data Visualization Examples of Effective Iteration Louise Heath: The Price of Oil versus Gold Wale Ilori: Air Quality Above America Paul Griffith: Le Tour de France Rodrigo Calloni: India’s Broken Toilets Sarah Bartlett: The Timing of Baby Making Daniel Caroli: The UK Economy Since the Brexit Vote Adolfo Hernandez: Baseball Demographics, 1947–2016 Giving and Receiving Feedback Giving Effective Feedback Receiving Feedback Summary Chapter 9 Effective Use of Color The Significance of Color in Data Visualization How Color Is Used to Tell Stories Using Color to Evoke Emotions Positive Results and Emotions Negative Results and Emotions Using Color to Create Associations Color Associations with Brands Color Associations with Topics Color Associations Across Multiple Charts Using Color to Highlight Best Practices for Using Color Less Is More Considerations for Color Blindness Using Background Colors Using Text as a Color Legend Summary Chapter 10 Choosing the Right Chart Type Area Charts Purpose Description Examples Alternatives Stacked Bar Charts Purpose Description Examples Alternatives Diverging Bar Charts Purpose Description Examples Alternatives Filled Maps Purpose Description Examples Alternatives Donut and Pie Charts Purpose Description Examples Alternatives Packed Bubble Charts Purpose Description Examples Alternatives Treemaps Purpose Description Examples Alternatives Slopegraphs Purpose Description Examples Alternatives Connected Scatterplots Purpose Description Examples Alternatives Circular Histograms Purpose Description Examples Alternatives Radial Bar Charts Purpose Description Examples Alternatives Resources Summary Chapter 11 Effective Use of Text Effective Titles and Subtitles Using Questions as Titles Making Definitive Statements Using Descriptive Titles Working with Quirky, Funny, and Poetic Titles Delivering on Your Promises What Is Your Key Message? State Your Message Semantics Matter Big Ass Numbers Call to Action Instructions and Explanations Filters Hover Interactivity Explanations Summary Chapter 12 Using Context to Inform The Importance of Context Lack of Context Using Simple Metrics Big Ass Numbers Color Coding Reference Lines Tooltips Subtitles Methods for Communicating Context Indicators and Arrows Comparing Time Periods Normalizing the Data Supplementing the Data Summary Part III The Community Long-Term Contributors Educators Employers Organizations Nonprofits Social Impact Makeover Monday Live Events Makeover Monday Enterprise Edition Source Lines Index EULA