MakeoverMonday improving how we visualize and analyze data, one chart at a time
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 an...
| Otros Autores: | , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
Wiley
2018.
|
| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630535506719 |
Tabla de Contenidos:
- 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
- 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.
