ggcorrplot2 | Implementation of corrplot using ggplot2 | Data Visualization library

by caijun R Version: Current License: MIT

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kandi X-RAY | ggcorrplot2 Summary

ggcorrplot2 is a R library typically used in Analytics, Data Visualization applications. ggcorrplot2 has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Reinventing wheels is not what I like doing. corrplot is a great R package, but I am really tired of customizing the appearance of corrplot, for example, the space between colorbar and its tick labels, the space around the plot that I don’t know how to control when writing it to PDF on my macOS. This is most likely because I am more familiar with the Grammar of Graphics implemented in ggplot2 than the base plotting system in R. There are several R packages (e.g., ggcorrplot developed by Alboukadel Kassambara, ggcorr developed by François Briatte) that can visualize a correlation matrix into a corrgram using ggplot2; however, they are unable to visualize a correlation matrix using ellipse and mixed methods. ggcorrplot2 has implemented only a subset of features of corrplot to meet my urgent needs. See examples in the Getting started section. More functionality will be added in the future as needed.

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ggcorrplot2 has a low active ecosystem.

It has 18 star(s) with 7 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ggcorrplot2 is current.

Quality

ggcorrplot2 has 0 bugs and 0 code smells.

Security

ggcorrplot2 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

ggcorrplot2 code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ggcorrplot2 is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

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ggcorrplot2 releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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ggcorrplot2 Key Features

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ggcorrplot2 Examples and Code Snippets

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Community Discussions

Trending Discussions on ggcorrplot2

ggcorrplot2 shows different significance asterisks

QUESTION

ggcorrplot2 shows different significance asterisks

Asked 2021-Oct-13 at 07:40

does anybody have an idea why ggcorrplot2 shows different significance asterisks than ggcorrplot? Very confusing to me.

https://github.com/caijun/ggcorrplot2

...

ANSWER

Answered 2021-Oct-13 at 07:40

data(mtcars)
cor.matrix <- corr.test(mtcars,method = "spearman", adjust = "BH", alpha = 0.05, ci = F)
corr <- cor.matrix[["r"]]
p.mat <- cor.matrix[["p"]]
p.mat[lower.tri(p.mat)] <- t(p.mat)[lower.tri(p.mat)] #to get only the adjusted p.Values symmetrically over the plot

p.mat[lower.tri(p.mat, diag = T)] <- 1 #to set the lower triangle to 1 (this way the asterisks wont be displayed on this part of the graph)
corrplot.mixed(corr, order= "original",mar=c(0,0,2,0), tl.col = 'black', p.mat = p.mat, insig = "label_sig", sig.level = c(.001, .01, .05), pch.cex=1.5, tl.cex = .8, number.font=2, number.cex=0.8)

Source https://stackoverflow.com/questions/69539460

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install ggcorrplot2

Get the development version from github:.
The mtcars dataset will be used to demonstrate the usages of ggcorrplot2. Most parameters of ggcorrplot2 functions are the same as those of corrplot. Therefore, it’s easy for users to migrate from corrplot to ggcorrplot2. The above examples reproduce some features of corrplot. In the following example, the added advantages of implementing corrplot using ggplot2, such as customizing the appearance of corrgram, combining a corrgram with other plots (including non-corrgrams) into one plot using cowplot, are demonstrated.