Visual inspection is a crucial part of "getting to know your data". A lot can be learned by examining univariate and multivariate charts and graphics. Looking at numeric and descriptive summaries of the data is important, but often characteristics of your data are not fully revealed until you look at your data and visual some summaries of the information contained in your variables.
Base R offers great features for data visualization. These are especially good for when you to do a quick scan of your data or if you do not want load any libraries.
ggplot2 is the most popular data visualization package in the R community and will allow you to create elegant and aesthetically pleasing graphics.
This tutorial focusses on exposing this underlying structure you can use to make any ggplot.
An outstanding summary of how to create almost every graphic imaginable in R
Business Science- gghalves: Make hybrid (half boxplot + half dotplot) visualizations with ggplot2 (8:15)
Business Science: patchwork- The ggplot2 plot combiner (9:28)
Business Science: rayshader- ggplot2 in 3D (8:43)
A 'shiny' gadget to create 'ggplot2' figures interactively with drag-and-drop to map your variables to different aesthetics. You can quickly visualize your data accordingly to their type, export in various formats, and retrieve the code to reproduce the plot.
DATAcated- Esquisse - drag and drop data visualization in R (3:48)
Business Science- esquisse: ggplot2 builder with Tableau Drag-and-Drop Interface (9:57)
InfoWorld- Esquisse - R tip: Drag-and-drop ggplot (7:52)
Radiant is an open-source platform-independent browser-based interface for business analytics in R. The application is based on the Shiny package and can be run locally or on a server.
Introducing Radiant (6:26)
Introduction to Radiant - Playlist
Radiant Tutorial Series- Playlist