A data visualization book list will remain incomplete if missing Tufte's books. Edward Tufte, with his beautiful design of the book and charts, has led the charge against bad data visualization a.k.a chart junk.

Cole Kanflic's Storytelling with data is a great addition to the collection of data visualization books. It is beginner-friendly and does not assume the knowledge of any programming. Most, if not all, the charts in the book can be created in Excel. The result is pleasing to the eyes and is clutter-free.

The charts in this book have more of an infographic-y feel to them -- but that's not a negative. I have advocated for simplicity and clarity and criticized "interesting" things, but often you need to splash the charts with some design elements to gain attention. This book provides you great examples of such charts.

Dona Wong, a former graphics editor at the Wall Street Journal and Tufte's student, gives concise advice on colors, chart types, and clarity. This book is my first recommendation for anyone interested in data visualization.

The big book of dashboards provides a great introduction to key data visualization principles and then presents valuable examples of dashboards that you may see in real life.

In the fundamentals of data visualization, Wilke shows countless examples that differentiate a good chart from a bad chart. This book is special because Wike created his own plotting style available via an R package.

Observe, collect, draw is a special book. One of my design professors recommended it to me. While it is not strictly a data visualization book of Tufte or Few variety, it provides great examples of how even simple data can be viewed with the help of a graphic. This book is great for ideation.

Alberto Cairo offers many examples of how the chart creators knowingly or unknowingly "lie." He shows how they do this: using faulty axis starting points, aspect ratios, and outright wrong data. This book will help you see how charts can manipulate certain emotions, and you will learn to question or avoid such charts.

Yes, I co-wrote this book. Yes, I am biased. The data visualization chapter in this book is so detailed and long that it could have become a separate book. I wrote about principles of effective data visualization, summarizing my learnings from the books before me. I advised which charts to use. And I provided detailed R code to create your own effective graphics.