MakeoverMonday : improving how we visualize and analyze data, one chart at a time / Andy Kriebel, Eva Murray.

Format:

Book

Author/Creator:

Kriebel, Andy, author.

Murray, Eva, author.

Language:

English

Subjects (All):

Information visualization.

Statistics.

Statistics as Topic.

Physical Description:

1 online resource (xvi, 472 pages) : illustrations

Edition:

1st edition

Other Title:

MakeoverMonday

Makeover Monday

Place of Publication:

Hoboken, New Jersey : Wiley, 2018.

System Details:

text file

Summary:

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.

Contents:

Intro

#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

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

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

Chapter 5 Attention to Detail

Typos

Punctuation

Formatting

Formatting Charts Effectively

Universal Formatting

Crediting Images and Data Sources

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

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

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

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

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

Chapter 10 Choosing the Right Chart Type

Area Charts

Purpose

Description

Examples

Alternatives

Stacked Bar Charts

Diverging Bar Charts

Filled Maps

Donut and Pie Charts

Packed Bubble Charts

Treemaps

Slopegraphs

Connected Scatterplots

Circular Histograms

Radial Bar Charts

Resources

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

Chapter 12 Using Context to Inform

The Importance of Context

Lack of Context

Using Simple Metrics

Color Coding

Reference Lines

Tooltips

Subtitles

Methods for Communicating Context

Indicators and Arrows

Comparing Time Periods

Normalizing the Data

Supplementing the Data

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.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781119510796

1119510791

9781119510727

1119510724

OCLC:

1057237250