After reading "Data Visualization Fundamentals"

This book was a much easier read than I expected. There isn't anything programming or mathematical in the book, but it was valuable to me and filled a missing piece of the puzzle in my knowledge.
This book introduces various main chart types and corresponding applicable scenarios by category, and gives various good and bad design demonstrations.
For me, there is no big difference between using pandas or echart or r to draw a picture. At most, it takes a few days to learn and check the manual. But behind the charts is the industry knowledge in the field of statistics. Many charts, before reading this book, I didn't know they existed, or I didn't know how to use them well.
For example, the relationship between color and grayscale. In the past, I only had a vague feeling, and I would unconsciously try some specific color combinations, but I never seriously understood this issue from the perspective of people with color weakness or color blindness. In the book, it is clearly given how to universally apply color design to a wide audience.
For another example, for the design of multi-dimensional charts, I only made some superficial attempts before, but in this book, there are very detailed introductions, especially how to ensure that the charts still have enough space after they are separated from the computer and printed on paper. expression ability.
The main text of the book is more than 300 pages. Among the books I have read recently, it can be regarded as a small book, without formulas and codes (the source code of the book uses R language, ggplot2 package, which can be downloaded separately). It is not a burden to read, but it is suitable for anyone who works or studies data-related people. Of course, to really get the job done, we need specific technical tools and solid statistical knowledge. But the understanding of visualization is also an essential part. This book can help us to be targeted.