Top Three Quotes
- “Visualization isn’t just about getting the cold hard facts. It’s also about feeling.”
- “You can find stories that you might never have found with just formal statistical methods.”
- “It’s not that the numbers lie. It’s the people who use the numbers who lie.”
Book Theme
Telling stories through data visualization. Visualize This explores how to make raw data understandable, beautiful, and compelling by using visual tools to uncover and communicate the stories hidden in the numbers.
Why You Should Read This Book
If you work with data—whether as a marketer, researcher, journalist, designer, or developer—this book will equip you to move beyond spreadsheets and create meaningful visuals that reveal the underlying narrative.
Key Ideas and Arguments Presented
- Data tells stories—visualization helps communicate them.
- Good design enhances clarity and emotion.
- Visualization is a skill anyone can learn through practice.
- The audience and purpose guide design decisions.
- Use the right tools for your specific data needs.
- Clean data is foundational to visualization.
- Always ask: what story does this visualization tell?
- Provide context—don’t rely on visuals alone.
- Maps and timelines add crucial dimensions.
- Creativity and humor can enhance engagement.
Book Outline
- Introduction
- Telling Stories with Data
- Handling Data
- Choosing Tools to Visualize Data
- Visualizing Patterns over Time
- Visualizing Proportions
- Visualizing Relationships
- Spotting Differences
- Visualizing Spatial Relationships
- Designing with a Purpose
Key Takeaways
- Visualization is the bridge between raw data and human understanding.
- Effective visuals serve a purpose, not just aesthetics.
- Good design starts with knowing your data inside and out.
- Practice and experimentation are essential to mastering this skill.
Key Techniques
- Cleaning and formatting data (Python, Excel)
- Choosing visualization tools (R, Illustrator, JavaScript)
- Using small multiples to show change
- Applying encoding and visual hierarchy
- Incorporating spatial and temporal dimensions
Author’s Qualifications
Nathan Yau is a statistician and creator of FlowingData.com. He holds a Master’s degree from UCLA and is completing a Ph.D. focused on visualization. He’s worked with The New York Times, CNN, and other leading organizations.
Comparison to Similar Books
This book is more hands-on than Edward Tufte’s work and more technical than Storytelling with Data by Knaflic. It offers a perfect middle ground for practitioners looking to both learn tools and understand design thinking.
Target Audience
- Data analysts and scientists
- Journalists and storytellers
- Graphic designers and UI/UX professionals
- Business intelligence professionals
- Policy analysts and researchers
- Educators teaching data literacy
- Developers building data-driven tools
Critical Response to the Book
Critics appreciated its practical focus and friendly tone. While some advanced users may find it too basic, it’s widely regarded as a strong foundational resource for newcomers and intermediate data visualizers.
One Sentence Takeaway
The best data visualizations don’t just show numbers—they tell stories that change how we see the world.