Data viz is both an art and science. Doing creating data viz is not the same as knowing how to create data viz. Books may not be accessible to many for reasons, like budgetary and logistical concerns. However, with access to the Internet, some gaps in terms of accessibility can be closed. The following blogs are worthy of a follow for knowledge that usually exists in books you need to buy. They are also not as heavily mentioned on lists of data viz blogs to follow that I have come across.
1. Nightingale at https://nightingaledvs.com/
Nightingale is the journal of the Data Visualization Society (DVS). It is full of articles on topics in data viz. From how to design a dashboard for business intelligence to discussions on issues via data journalism and from seeing data as art to the history of data viz. For whatever your interest is in data viz, there is an article for you. This is largely due to it being run by a team of dedicated volunteers and articles can be contributed from the community. Thus, if you have an article for them to publish, you can make your pitch!
2. Datawrapper at https://blog.datawrapper.de/
A blog by the Datawrapper team. In addition to updates on the Datawrapper app, it has articles on various topics from do's and don'ts and weekly charts. Most importantly, it also has a weekly round up of data viz of charts from around the web. This will allow you access many inspirational viz at one place. Consistently updated, the blog can be added into your routine to learn not only about data viz, but also see the world through data viz.
3. Questions in Dataviz at https://questionsindataviz.com/
A blog by Neil Richards. Although Richards is a Tableau practitioner, his blog goes into data viz outside of just the tool he uses. He writes about colours in data viz, books on data viz, and his thoughts on visualising data. Richards' reflections provide a sort of a key to unlock deeper thoughts on the topics in data viz in your mind. The title of the blog is truly accurate.
All in all, practice is just a part of the data viz equation. By reading, you can know more. Happy reading and learning!