Not sure if the book is the ideal format for this, but it seems to have the highest chance of being competent, unbiased and comprehensive. For the latter point, I think important topics are
- Colors and accessibility
- Concrete examples of color schemes
- Pros and Cons of different visualizations vis-à-vis data
- Print versus digital
- Fonts and layout considerations
- Perhaps short insights into the research on these points
But perhaps there are other things not on my radar that are current or interesting?
1. The Visual Display of Quantitative Information - Edward Tufte
2. Storytelling With Data
3. Documentation pages of data Viz tools e.g. 1, 2, 3 depending on your programming language of choice.
IMHO python ecosystem is still struggling with solid visualization as compared to JavaScript and R. Ggplot gives you shiny Viz but I'm not a fan of R.
D3 and it's derivatives are awesome for dynamic Viz if that's what you are after. GL
1. https://github.com/d3/d3/wiki
Cleveland worked at Bell Labs and his work is timeless and very practical. It isn't about artwork or making things look nice. It's about communicating information. I like to contrast his work with Tufte's. Tufte comes up with some nice stuff but I find it to be more art than science where the information is clearly sacrificed to ascetics. With visualizations I always ask myself, "Do you know more now about what is going on than you did before or is it just something nice to look at?" Way too often it's the latter.
[1] https://www.amazon.com/Elements-Graphing-Data-William-Clevel...
[2] https://www.amazon.com/Visualizing-Data-William-S-Cleveland/...
The Visual Display of Quantitative Information - Edward Tufte
The Grammar of Graphics - Leland Wilkinson
FlowingData's guides - https://flowingdata.com/category/guides/
But from your list I gather that you're more interested in the visual design of things (colour schemes, fonts etc); if that's the case you can search for resources on visual/graphic design which I don't know too much about. I can say that the choice of fonts and colours is a small part of data visualisation - very few basic princpiples, using a tool with good defaults and some common sense get you a very long way. The bigger part is deciding which parts of your dataset to communicate in what way and the resources that I mentioned are pretty good at teaching you that.
Better Data Visualizations by Jonathan Schwabish is the best. He combines all the insight from recent data biz books like Storytelling with Data or Cairos series into a comprehensive guide. Even has a practical section on visualizing qualitative data, which I never see.
And she co-wrote a beautiful book with Shirley Wu: https://www.datasketch.es/
Several of the other comments, such as Wilkinson's GoG or Cleveland's research, I don't think make sense as an intro to the topic. I have posted my notes on various data viz books (which are quite heterogenous) in this blog post: https://andrewpwheeler.com/2020/11/04/overview-of-dataviz-bo...
You should take a look into this.
> Without minimizing the value of intuition as a problem solving tool, we propose that systematic design programs are more valuable from a communication standpoint than ad hoc solutions; that intention is preferable to accident; that principled rationale provides a compelling basis for design decisions than personal creative impulse.
Cole is an excellent teacher and is able to clearly share exactly what practitioners need to know to make meaningful visualizations.
Take a look at the table of contents on that link, it could be a good fit for what you're looking for.
The "Book of Circles" and "Book of Trees" are also good.