Complete Guide to 3D Plots in R: Static and interactive 3-dimension graphs

Alboukadel KASSAMBARA

Alboukadel KASSAMBARA

Giới thiệu về sách điện tử này

This book provides a complete guide for visualizing a data in 3 dimensions (3D) using R software. It contains 2 main parts and 7 chapters describing how to draw static and interactive 3D plots.   
   
- The chapter 1 is about data preparation for 3D plot
- In chapter 2, we describe how to create easily basic static 3D scatter plots. We provide R codes for changing: 1) main and axis titles; 2) the appearance of the plot (point colors, labels and shapes, legend position, ...)
- Chapter 3 presents how to create advanced static 3D plots including 3D scatter plots with confidence interval, 3D line plots, 3D texts, 3D barplots, 3D histograms and 3D arrows.
- Chapter 4 describes the required package for drawing interactive 3D plots.
- In chapter 5, we show how to transform easily an existing static 3D plot into aninteractive 3D plot.
- Chapter 6 provides many examples of R codes for creating interactive 3D scatter plotswith 3D regression surfaces and concentration ellipsoids. We describe also how to exportthese graphs as png or pdf files.
- Chapter 7 presents a complete guide to RGL 3D visualization device system. We provide also R codes for creating a movie from RGL 3D scene and for exporting plot into an interactive HTML web file.
    
Each chapter is organized as an independent quick start guide. This means that, you don’tneed to read the different chapters in sequence.

Giới thiệu tác giả

 Alboukadel Kassambara is a PhD in Bioinformatics and Cancer Biology. He works since many years on genomic data analysis and visualization. He created a bioinformatics tool called GenomicScape (www.genomicscape.com) which is an easy-to-use web tool for gene expression data analysis. He developed also a website called STHDA (Statistical Tools for High-throughput Data Analysis, www.sthda.com), which contains many tutorials on data analysis and visualization using R software and packages. He is the author of the R package factoextra which can be used to easily extract and visualize the results of multivariate analysis such PCA, CA, MCA and clustering.