Next to the discussed plotting libraries so far, there are of course many more plotting libraries available on CRAN, GitHub or elsewhere. However, before we end this section we want to mention just some more plotting libraries, which we found quite useful.

GGally extends ggplot2 by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks. Visit the package’s vignette for a demonstration of the functionality of this package.

ggfortify provides data visualization tools for statistical analysis results. It unifies plotting tools for statistics commonly used, such as GLM (generalized linear models), time series, PCA (principal component analysis) families, clustering and survival analysis. The package offers a single plotting interface for these analysis results and plots them in a unified style using ggplot2. Visit the introductory vignette or the vignette on plotting of geospatial data for a demonstration of the functionality of this package.

Plotting the correlation of multiple variables is one of the most informative forms of data visualization. Here we want to recommend two very powerful packages, which however are doing mainly the same thing. The corrplot and the corrgram packages both visualize correlation matrices. Visit the vignettes of both packages (corrplot vignette and corrgram vignette) to see some use cases of these libraries.

hexbin provides binning and plotting functions for hexagonal bins. Hexagon binning is a form of bivariate histogram useful for visualizing the structure in large to very large data sets.

dygraphs provides an R interface to the dygraphs JavaScript charting library. The package provides rich facilities for charting time-series data in R, including highly configurable series- and axis-display and interactive features like zoom/pan and series/point highlighting. Check out the webpage of dygraphs for R and enjoy the great gallery with amazing interactive graphs and plots.

shiny is an R package that makes it easy to build interactive web apps straight from R. You can host standalone apps on a webpage or embed them in R Markdown documents or build dashboards. shiny makes it easy to build beautiful, responsive and powerful applications with minimal effort. Check out the shiny gallery, which provides amazing examples for interactive data visualization.

Citation

The E-Learning project SOGA-R was developed at the Department of Earth Sciences by Kai Hartmann, Joachim Krois and Annette Rudolph. You can reach us via mail by soga[at]zedat.fu-berlin.de.

Creative Commons License
You may use this project freely under the Creative Commons Attribution-ShareAlike 4.0 International License.

Please cite as follow: Hartmann, K., Krois, J., Rudolph, A. (2023): Statistics and Geodata Analysis using R (SOGA-R). Department of Earth Sciences, Freie Universitaet Berlin.