As the days grow shorter and the weather colder, one of our favorite things to do is to wrap up warm and sit down with a cup of tea and a book. As avid readers, we wanted to find a way to combine our love of books with our passion for data visualization. We set out to read a variety of books throughout the year and then create visualizations that capture the essence of each book. In this post, we’ll share some of our favorite visualizations and give you a glimpse into our process.
So, if you’re a book lover who loves data visualization (or vice versa), you’re in the right place! Let’s dive into the world of data-driven storytelling.
Earlier this year, I read Jonathan Franzen’s latest book, Crossroads, and was inspired to visualize the interactions between the characters. As the first of a three-part saga, the book follows the Hildebrandt family through the 70s Midwest. With each chapter written from a different family member’s perspective, I wanted to track who was talking to whom and who was the focus of each chapter. The result? A beautiful chord diagram that reveals the key players and their relationships in the story. It’s a powerful reminder of the potential of data visualization to help us understand and interpret complex data. Plus, it’s just plain cool to see the characters and their interactions come to life in this way.
Another book I read this year was Anthony Bourdain’s bestselling memoir, Kitchen Confidential. I couldn’t resist visualizing the delicious foods mentioned throughout the book. As a fan of Bourdain’s curious, humble, and sometimes dark writing style, I was excited to dig into this behind-the-scenes look at his life as a professional chef. And what better way to explore the book than by tracking all the delicious foods mentioned within its pages? Using our “Survey” template as well as our premium “Data explorer”, I tracked all the foods mentioned in the book and categorized them by type in the scrollytelling piece below. It’s a fun and unique way to explore the book and highlight the insights that data visualization can provide.
If you’ve ever walked past a bookstore and been drawn in by a book that’s been on display for weeks, you’ll understand why I picked up Where The Crawdads Sing. Despite being a novel about seagulls (which, let’s be honest, doesn’t sound that exciting), the book has garnered a ton of attention, praise and even a Hollywood film adaptation. And for good reason!
Let me start by saying that there were many special things about “Where The Crawdads Sing”. In fact, it is so much more than a book about seagulls (although they’ve been mentioned almost 50 times throughout). The novel follows Kya or the “Marsh Girl” as she grows up alone in a North Carolina swamp in the early 1950s. Abandoned by her whole family, Kya has no other choice but to learn from her surroundings – a habitat engulfed by gulls, bullfrogs and herons. We get to see how solitude influences a woman’s behavior who shares our genetic desire to belong but is forced to be alone.
It comes as no surprise that a book based in the wilderness will surely talk about animals. There have been 612 mentions of animals throughout the novel (if I counted correctly), sometimes simply acknowledging Kya’s non-human neighbors, and at times even used as an offense: “Where’s yo’ hat, swamp rat?”
Considering Kya’s lifetime reluctance to leave the marshlands, I was intrigued to find out which animals became her most trusted companions, which were mostly used for food, and which appear more often in our speech than we expect. To analyze this, I used the “Data explorer” template.
Where The Crawdads Sing is a captivating novel that not only tells an engaging story, but also offers a unique look at the relationship between a young woman and the wildlife that surrounds her. Through the use of data visualization, I was able to analyze the frequency and significance of the various animal species mentioned in the novel. Like a dazzling summer sunset, “Where The Crawdads Sing” is both humble and breathtaking.
In 2021, the year after I graduated university, I decided to set myself a reading challenge. When I was younger you would hardly ever find me without my nose in a book, but during my time at university I’d been so busy with readings for essays (and nights out) that I got out of the habit of reading. So, to get myself back into books I decided to set myself the (slightly crazy) goal to read 100 books in a year.
I didn’t manage to hit this goal in 2021 - I only made it to book 66, but as we speak I am currently reading book 96 of 100, with just under 3 weeks left of the year. 100 books is a lot of pages, and even with 5 books left to finish, I have managed to read nearly 40,000 pages in the past 12 months.
As I was reflecting on my reading habits, I became curious about how my ratings compared to those of others, so I took a look at the data on Goodreads. Goodreads is a popular platform among book lovers for reviewing, rating and recommending books to each other. I decided to take a closer look at the data and see if I am a generous or critical rater.
One interesting finding was that, despite reading more romance novels than any other genre this year, I tend to rate them lower than their average Goodreads score. This could indicate that I have higher standards for romance novels, or that I am less likely to be swept away by the usual tropes and clichés of the genre.
On the other hand, I tend to rate non-fiction books much higher than other Goodreads users, despite only reading 7 books in this genre this year. This could mean that I am particularly impressed by the non-fiction books I choose to read, or that I have a special appreciation for the insights and knowledge that they provide.
To illustrate the comparison between the Goodreads users’ and my ratings further, I decided to show my ratings and the average Goodreads ratings with the biggest difference between them in a connected dot plot visualization. This allows me to see the distribution of ratings for each title, as well as the differences between my ratings and the average. The connected dot plot is a useful visualization for emphasizing the difference between two or more data series due to the visual connection between the dots.
Finally, I grouped all of my books from 2022 in a radial tree to show my main genres and authors as well as the ratings I gave each book.
Overall, 2022 has been a great year for books and I’ve definitely found my passion for reading again. Shall we make the goal for 2023 to read 200? (No).
Click through the story to find my favorites!
At the beginning of this year, I read All The President’s Men, Woodward and Bernstein’s account of the Watergate scandal and their Pulitzer Prize-winning reporting for The Washington Post. Much of the story follows the journalists as they gradually uncover the ever-widening web of people involved, from the initial burglary to the cover-up and investigations that followed. I found myself constantly referring back to the “cast of characters” found at the start of the book to remind myself who was who, so I decided to create a network graph of these characters, tracing how they are all connected and how the story was revealed.
Another interesting aspect of the Watergate story was how long the investigations went on for, with over two years between the initial Watergate burglary and President Nixon’s resignation. Woodward and Bernstein’s follow up book, “The Final Days” — which I’m currently reading — begins with a chronology of the saga, which I’ve recreated using our “Timeline” template.
Donna Tartt’s book is a captivating tale of a group of misfits at an elite New England college who are influenced by their charismatic classics professor. As they discover a new way of thinking and living, they also venture beyond the boundaries of normal morality, leading to a descent into corruption and betrayal.
I chose to visualize this book because of the rich descriptions and the central role that color plays in bringing the characters and scenes to life. By focusing on the colors mentioned in the first two chapters, I was able to uncover hidden patterns and trends, such as the predominant use of black and white for garments and the frequent use of red to describe people, particularly female characters.
But it’s not just about the colors themselves – our visualization also allows readers to explore the associations and character identities that are built through the use of color. For example, Charles and Camilla Macaulay stand out in campus with their predominantly white attire, while Francis Abernathy exudes a “Dark Academia” vibe with his long black coats and cigarette.
Overall, our data visualization provides a unique and deeper look at the role of color in Tartt’s book, and allows readers to uncover insights and patterns that may have been overlooked in a traditional reading experience.
As we’ve explored in this post, data visualization can be a powerful tool for enhancing our understanding and appreciation of the books we read. By combining our love of literature with our passion for data visualization, we’ve been able to uncover hidden patterns, trends, and insights that might have been overlooked in a traditional reading experience. From the complex relationships between the characters in Crossroads, to the delicious foods mentioned in Kitchen Confidential, to the impact of seagulls on the story in Where The Crawdads Sing, data visualization allows us to delve deeper into the books we love and uncover new layers of meaning
If you’ve ever wanted to create your own book-related visualizations, now is the time! Whether you’re a beginner or an expert, we invite you to share your own creations with us. We’d love to see what you come up with, and we’re excited to see how data visualization can bring your favorite books to life. Happy reading and visualizing!