Beginning Data Visualization with R is Matthew Renze’s second course on R for Pluralsight, and it follows from the first on exploratory data analysis (review here). In this second course, Matthew takes a look at univariate and bivariate data visualization.
The flow of the course is similar to the first course: Matthew’s examples are based around a fictitious company and uses the Open Movie Database for raw data. In this particular course, we spend less time learning about transformations and more about the three biggest graphics systems within R: the base R graphics library, Lattice, and ggplot2. Matthew does a good job of showing how to create various forms of plots on these different libraries, showing when to use each type (e.g., box plots, bar graphs, and scatter plots). He also shows cases in which certain libraries do not have particular graph types.
I think this was a great course. If I had one knock, it’s that some of the examples suffered due to the data set. For example, Matthew showed us heatmaps and density plots of the number of movies by runtime. The plot did work and it did show what you can do, but I would have preferred to see him use a data set with at least two clusters so you can really get the power of these types of charts.
Regardless of that minor complaint, if you are interested in learning how to perform visualizations with R, this is a great course. I’m looking forward to his intermediate and advanced-level (forthcoming) courses as well.