Data Visualization
Previously, we described the essentials of R programming and provided quick start guides for importing data into R.
This chapter describes how to plot data in R and make elegant data visualization.
How this chapter is organized?
Lattice Graphs
Lattice package is a powerful and elegant data visualization system that aims to improve on base R graphs.
- xyplot(): Scatter plot
- cloud(): 3D scatter plot
- Box plot, Dot plot, Strip plot
- Density plot and Histogram
Read more: —> Lattice Graphs.
Ggplot2
ggplot2 is a powerful and a flexible R package, implemented by Hadley Wickham, for producing elegant graphics.
- ggplots
- ggplot2 Graphical Parameters
- Main title, axis labels and legend title
- Legend position and appearance
- Change colors automatically and manually
- Point shapes, colors and size
- Add text annotations to a graph
- Line types
- Themes and background colors
- Axis scales and transformations
- Axis ticks: customize tick marks and labels, reorder and select items
- Add straight lines to a plot: horizontal, vertical and regression lines
- Rotate a plot: flip and reverse
- Faceting: split a plot into a matrix of panels
- Cheat Sheets
Read more: —> ggplot2 essentials.
3D Graphics
3d scatter plot rgl
- Static 3D Scatter Plots
- Interactive 3D Graphs
Read more: —> 3D Graphics.
Infos
This analysis has been performed using R statistical software (ver. 3.2.4).
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Recommended for You!
Recommended for you
This section contains the best data science and self-development resources to help you on your path.
Books - Data Science
Our Books
- Practical Guide to Cluster Analysis in R by A. Kassambara (Datanovia)
- Practical Guide To Principal Component Methods in R by A. Kassambara (Datanovia)
- Machine Learning Essentials: Practical Guide in R by A. Kassambara (Datanovia)
- R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia)
- GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia)
- Network Analysis and Visualization in R by A. Kassambara (Datanovia)
- Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia)
- Inter-Rater Reliability Essentials: Practical Guide in R by A. Kassambara (Datanovia)
Others
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham & Garrett Grolemund
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Géron
- Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce & Andrew Bruce
- Hands-On Programming with R: Write Your Own Functions And Simulations by Garrett Grolemund & Hadley Wickham
- An Introduction to Statistical Learning: with Applications in R by Gareth James et al.
- Deep Learning with R by François Chollet & J.J. Allaire
- Deep Learning with Python by François Chollet
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Categories contained by this category :
3D graphics
ggplot2 - Essentials
R Base Graphs
Articles contained by this category :
Lattice Graphs
The Elements of Choosing Colors for Great Data Visualization in R