taiyun / Corrplot

Summary

The R package corrplot is for visualizing correlation matrices and confidence intervals. It also contains some algorithms to do matrix reordering. For examples, see its vignette.

This package is licensed under GPL, and available on CRAN: http://cran.r-project.org/package=corrplot.

How to cite

The R core development team and the very active community of package authors have invested a lot of time and effort in creating R as it is today. Please give credit where credit is due and cite R and R packages when you use them for data analysis. To cite corrplot properly, call the R built-in command citation("corrplot") as follows:

library(corrplot)
citation("corrplot")

Basic example

library(corrplot)
M <- cor(mtcars)
corrplot(M, order = "hclust", addrect = 2)

Download and Install

To download the development version of the package, type the following at the R command line:

install.packages("devtools")
devtools::install_github("taiyun/corrplot", build_vignettes = TRUE)

To download the release version of the package on CRAN, type the following at the R command line:

install.packages("corrplot")

How to contribute

• Fork, clone, edit, commit, push, create pull request
• Use RStudio
• Unit-testing: press CTRL+SHIFT+T in RStudio
  • we know that is hard to write tests especially for a visual package like this

Reporting bugs and other issues

If you encounter a clear bug, please file a minimal reproducible example on github.

How to perform static code analysis and style checks

We use lintr which also performs the analysis on Travis-CI. Configuration for lintr is in .lintr file. Lints are treated as warnings, but we strive to be lint-free.

In RStudio, you can run lintr from the console as follows:

> lintr::lint_package()

Who do I talk to?

• Taiyun Wei (main)
• Viliam Simko (backup)

License

This package is free and open source software, licensed under MIT

Other links

• Corrplot listed at OpenHub: https://www.openhub.net/p/corrplot
• Research software impact of Corrplot (by Depsy): http://depsy.org/package/r/corrplot
• CRAN: http://cran.r-project.org/web/packages/corrplot