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authorGlenn Johnson <glenn-johnson@uiowa.edu>2021-01-16 08:16:49 -0600
committerGitHub <noreply@github.com>2021-01-16 15:16:49 +0100
commit0dbdfa20ae2066ec215597cd08b1712360b1a882 (patch)
tree1c42c0e26e2bae0bbfbf68166cff89398c98fd6d
parent7c5ea8d3b458c28396d74e126329117862b367e1 (diff)
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add version 1.0.7 to r-factoextra (#20945)
-rw-r--r--var/spack/repos/builtin/packages/r-factoextra/package.py13
1 files changed, 11 insertions, 2 deletions
diff --git a/var/spack/repos/builtin/packages/r-factoextra/package.py b/var/spack/repos/builtin/packages/r-factoextra/package.py
index 6de3ee5bb0..48e4884a14 100644
--- a/var/spack/repos/builtin/packages/r-factoextra/package.py
+++ b/var/spack/repos/builtin/packages/r-factoextra/package.py
@@ -7,13 +7,22 @@ from spack import *
class RFactoextra(RPackage):
- """factoextra: Extract and Visualize the Results of Multivariate Data
- Analyses"""
+ """Extract and Visualize the Results of Multivariate Data Analyses
+
+ Provides some easy-to-use functions to extract and visualize the output of
+ multivariate data analyses, including 'PCA' (Principal Component Analysis),
+ 'CA' (Correspondence Analysis), 'MCA' (Multiple Correspondence Analysis),
+ 'FAMD' (Factor Analysis of Mixed Data), 'MFA' (Multiple Factor Analysis)
+ and 'HMFA' (Hierarchical Multiple Factor Analysis) functions from different
+ R packages. It contains also functions for simplifying some clustering
+ analysis steps and provides 'ggplot2' - based elegant data
+ visualization."""
homepage = "http://www.sthda.com/english/rpkgs/factoextra"
url = "https://cloud.r-project.org/src/contrib/factoextra_1.0.4.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/factoextra"
+ version('1.0.7', sha256='624ff01c74933352aca55966f8a052b1ccc878f52c2c307e47f88e0665db94aa')
version('1.0.5', sha256='8177a3f5107883ae248b2cd0afa388a1794741f5155a9455b3883788cf44d5d0')
version('1.0.4', sha256='e4a000a04ef5b9aa0790dc6e5277451c482a19ba10dda9474f6c6982424aeed3')