Since the moment I accepted to contribute to this book, I knew I wanted the chapter to be full of examples. After all, looking at examples is one of the best ways to learn, right? In my case, examples meant guiding the readers through the entire design process—from data analysis to visualisation. So I first needed a data set. I toyed with a few ideas and finally landed on something very meta: a list of data visualisation books everyone should read. The teams from Information is Beautiful and Data Visualisation Society have put such a list together and it's pretty awesome! The data they provide covers the names and categories of these books, their release dates and authors. But the more I analysed this data, the more questions I had about the authors: what is their background? how old were they when they published their first book? which countries do they come from? are they still alive? how many people have read or rated their books? etc. I spent a few days gathering all this data manually and decided to keep a few of the above-mentioned additional metrics. You can see the data visualised below, through the authors' angle. For more details on the design process of this visualisation, you can read this blog post.