linkspotter: Bivariate Correlations Calculation and Visualization

Compute and visualize using the 'visNetwork' package all the bivariate correlations of a dataframe. Several and different types of correlation coefficients (Pearson's r, Spearman's rho, Kendall's tau, distance correlation, maximal information coefficient and equal-freq discretization-based maximal normalized mutual information) are used according to the variable couple type (quantitative vs categorical, quantitative vs quantitative, categorical vs categorical).

Version:	1.3.0
Depends:	R (≥ 3.2.0)
Imports:	shiny, visNetwork, infotheo, minerva, energy, mclust, rAmCharts, pbapply, ggplot2, dplyr, tidyr, shinybusy
Suggests:	knitr, rmarkdown
Published:	2020-07-23
DOI:	10.32614/CRAN.package.linkspotter
Author:	Alassane Samba [aut, cre], Orange [cph]
Maintainer:	Alassane Samba <alassane.samba at orange.com>
BugReports:	https://github.com/sambaala/linkspotter/issues
License:	MIT + file LICENSE
URL:	https://github.com/sambaala/linkspotter
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	linkspotter results

Documentation:

Reference manual:	linkspotter.pdf
Vignettes:	Introduction to Linkspotter

Downloads:

Package source:	linkspotter_1.3.0.tar.gz
Windows binaries:	r-devel: linkspotter_1.3.0.zip, r-release: linkspotter_1.3.0.zip, r-oldrel: linkspotter_1.3.0.zip
macOS binaries:	r-release (arm64): linkspotter_1.3.0.tgz, r-oldrel (arm64): linkspotter_1.3.0.tgz, r-release (x86_64): linkspotter_1.3.0.tgz, r-oldrel (x86_64): linkspotter_1.3.0.tgz
Old sources:	linkspotter archive

Reverse dependencies:

Reverse suggests:

bullseye

Linking:

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