R Graphics Cookbook: Practical Recipes for Visualizing Data

This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.

Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started.

• Use R’s default graphics for quick exploration of data
• Create a variety of bar graphs, line graphs, and scatter plots
• Summarize data distributions with histograms, density curves, box plots, and other examples
• Provide annotations to help viewers interpret data
• Control the overall appearance of graphics
• Render data groups alongside each other for easy comparison
• Use colors in plots
• Create network graphs, heat maps, and 3D scatter plots
• Structure data for graphing

• R Cookbook (O'Reilly Cookbooks)
• R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
• ggplot2: Elegant Graphics for Data Analysis (Use R!)
• Learning R
• Practical Statistics for Data Scientists: 50 Essential Concepts
• Hands-On Programming with R: Write Your Own Functions And Simulations
• Applied Predictive Modeling
• An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
• Text Mining with R: A Tidy Approach
• The Art of R Programming: A Tour of Statistical Software Design