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factoextra : 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), MFA (Multiple Factor Analysis) and HMFA (Hierarchical Multiple Factor Analysis) functions from several packages : PCA, CA, MCA, MFA, HMFA [FactoMineR]; prcomp and princomp [stats]; dudi.pca, dudi.coa, dudi.acm [ade4]; ca [ca]; corresp [MASS]. It contains also many functions for simplifying clustering analysis workflows. The ggplot2 plotting system is used. See http://www.sthda.com/english/rpkgs/factoextra for more information, documentation and examples.

Installation

Install the latest version from GitHub

# Install
if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/survminer")

Geting started

Find out more at http://www.sthda.com/english/wiki/factoextra-r-package

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Version

Install

install.packages('factoextra')

Monthly Downloads

72,634

Version

1.0.3

License

GPL-2

Last Published

April 26th, 2016

Functions in factoextra (1.0.3)

fviz_contrib

Visualize the contributions of row/column elements
fviz_hmfa

Visualize Hierarchical Multiple Factor Analysis
fviz_dend

Enhanced Visualization of Dendrogram
fviz_silhouette

Visualize Silhouette Information from Clustering
fviz_mca

Visualize Multiple Correspondence Analysis
get_pca

Extract the results for individuals/variables - PCA
get_hmfa

Extract the results for individuals/quantitative variables/qualitative variables/group/partial axes - HMFA
fviz_add

Add supplementary data to a plot
fviz_pca

Visualize Principal Component Analysis
fviz_mfa

Visualize Multiple Factor Analysis
eigenvalue

Extract and visualize the eigenvalues/variances of dimensions
eclust

Visual enhancement of clustering analysis
get_mfa

Extract the results for individuals/quantitative variables/qualitative variables/group/partial axes - MFA
poison

Poison
fviz_cos2

Visualize the quality of representation of rows/columns
facto_summarize

Subset and summarize the output of factor analyses
print.factoextra

Print method for an object of class factoextra
fviz_ca

Visualize Correspondence Analysis
housetasks

House tasks contingency table
multishapes

A dataset containing clusters of multiple shapes
get_clust_tendency

Assessing Clustering Tendency
get_mca

Extract the results for individuals/variables - MCA
decathlon2

Athletes' performance in decathlon
hkmeans

Hierarchical k-means clustering
dist

Enhanced Distance Matrix Computation and Visualization
hcut

Computes Hierarchical Clustering and Cut the Tree
get_ca

Extract the results for rows/columns - CA
fviz_nbclust

Dertermining and Visualizing the Optimal Number of Clusters
fviz_cluster

Visualize Clustering Results