K. Healy, Data Visualization: A Practical Introduction (Princeton: Princeton University Press, 2018).
– An engaging read that manages to integrate ggplot2 code with key Information Visualization theory and using real social science datasets.
Free online (draft version).
R. Lovelace, J. Nowosad, and J. Muenchow, Geocomputation with r (London, UK: CRC Press, 2019).
– This book comprehensively introduces spatial data handling in R. It is a great complement to R for Data Science in that it draws on brand new libraries that support tidyverse-style
operations on spatial data.
Free online.
H. Wickham and G. Grolemund, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (Sebastopol, California: O’Reilly Media, 2017).
– The primer for doing data analysis with R. Wickham and Grolemund present a thesis of the data science workflow and illustrates how R and packages that form the tidyverse
support this. It is both accessible and coherent and is highly recommended.
Free online.
C. Wilke, Fundamentals of Data Visualization (Sebastopol, California: O’Reilly Media, 2019).
– Excellent resource – comprehensively covers key theory and important emerging areas of visual data analysis (uncertainty visualization etc. with an R and ggplot2
framing).
Free online.
Flowingdata
– Nathan Yau, a former statistics PhD from UCLA, has maintained a data vis blog and online training materials for some time. Numerous excellent examples, on the most part implemented in R and ggplot2
.
giCentre
– World-leading group researching and developing geovisualization. Check out recent work on litvis and elm-vega.
Multiple Views
– Blog series by leading visualization researchers and practitioners.
IEEE VIS
– The conference at which leading Data Visualization work is published through a special issue of Transactions on Visualization & Computer Graphics.
OpenVis Conf
– New, exciting conference (though last one was in 2018!). Presenters are academics and practitioners. Videos of talks from previous conferences are published online. From the 2018 conference, I’d recommend Matt Kay’s on Uncertainty Visualization, Maarten Lambrechts’ Xenographics and Heather Krause’s F-Word.