First off, O'Reilly programming books are well-known (enough to be parodied) and if you are interested in one of those specific books there's a good chance it's a good one. I am particularly drawn to the Python book, the two Stats books and all of the $1 books. I heard the R reference is a bit outdated, but I'm sure it can be better at explaining some parts than Stack Overflow and a bunch of R docs.
The 'Doing Data Science' book is basically a Data Science 101 course molded in book-form. I read the first part today. The author argues that a lot of people in academia and businesses are already doing data science, they just don't really see it that way. It is the very useful ability to manage, explore, analyse and visualize data. Unlike stats, data science requires that you combine those abilities with field knowledge to gain insight and solve real world problems. In my case, I want to use data science methods and concepts and apply it to transportation / urban problems.
I never thought of it that way. It made me realize that my master thesis checks all those boxes and that I totally need to explore data science more. From how you're describing what you do, it sounds to me like you could also do well to dive deeper into data science.