Package: factoextra 1.0.7.999

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), '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.

Authors:Alboukadel Kassambara [aut, cre], Fabian Mundt [aut]

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factoextra.pdf |factoextra.html✨
factoextra/json (API)
NEWS

# Install 'factoextra' in R:
install.packages('factoextra', repos = c('https://kassambara.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/kassambara/factoextra/issues

Datasets:

On CRAN:

14.14 score 355 stars 50 packages 14k scripts 92k downloads 650 mentions 83 exports 110 dependencies

Last updated 5 years agofrom:1689fc74b9. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-winNOTENov 08 2024
R-4.5-linuxNOTENov 08 2024
R-4.4-winNOTENov 08 2024
R-4.4-macNOTENov 08 2024
R-4.3-winOKNov 08 2024
R-4.3-macOKNov 08 2024

Exports:eclustfacto_summarizefvizfviz_addfviz_cafviz_ca_biplotfviz_ca_colfviz_ca_rowfviz_clusterfviz_contribfviz_cos2fviz_dendfviz_distfviz_eigfviz_ellipsesfviz_famdfviz_famd_indfviz_famd_varfviz_gap_statfviz_hmfafviz_hmfa_groupfviz_hmfa_indfviz_hmfa_ind_starplotfviz_hmfa_quali_biplotfviz_hmfa_quali_varfviz_hmfa_quanti_varfviz_hmfa_varfviz_mcafviz_mca_biplotfviz_mca_indfviz_mca_varfviz_mclustfviz_mclust_bicfviz_mfafviz_mfa_axesfviz_mfa_groupfviz_mfa_indfviz_mfa_ind_starplotfviz_mfa_quali_biplotfviz_mfa_quali_varfviz_mfa_quanti_varfviz_mfa_varfviz_nbclustfviz_pcafviz_pca_biplotfviz_pca_contribfviz_pca_indfviz_pca_varfviz_screeplotfviz_silhouetteget_caget_ca_colget_ca_rowget_clust_tendencyget_distget_eigget_eigenvalueget_famdget_famd_indget_famd_varget_hmfaget_hmfa_groupget_hmfa_indget_hmfa_partialget_hmfa_quali_varget_hmfa_quanti_varget_hmfa_varget_mcaget_mca_indget_mca_varget_mfaget_mfa_groupget_mfa_indget_mfa_partial_axesget_mfa_quali_varget_mfa_quanti_varget_mfa_varget_pcaget_pca_indget_pca_varhcuthkmeanshkmeans_tree

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacliclustercolorspacecorrplotcowplotcpp11crosstalkdendextendDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustfontawesomeFormulafsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpolynompromisespurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreshape2rlangrmarkdownrstatixsassscalesscatterplot3dSparseMstringistringrsurvivaltibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Athletes' performance in decathlondecathlon2
Deprecated Functionsdeprecated fviz_hmfa_group fviz_hmfa_ind_starplot fviz_hmfa_quali_var fviz_hmfa_quanti_var fviz_mfa_group fviz_mfa_ind_starplot fviz_mfa_quali_var fviz_mfa_quanti_var get_hmfa_group get_hmfa_quali_var get_hmfa_quanti_var get_mfa_group get_mfa_quali_var get_mfa_quanti_var
Enhanced Distance Matrix Computation and Visualizationdist fviz_dist get_dist
Visual enhancement of clustering analysiseclust
Extract and visualize the eigenvalues/variances of dimensionseigenvalue fviz_eig fviz_screeplot get_eig get_eigenvalue
Subset and summarize the output of factor analysesfacto_summarize
Visualizing Multivariate Analyse Outputsfviz
Add supplementary data to a plotfviz_add
Visualize Correspondence Analysisfviz_ca fviz_ca_biplot fviz_ca_col fviz_ca_row
Visualize Clustering Resultsfviz_cluster
Visualize the contributions of row/column elementsfviz_contrib fviz_pca_contrib
Visualize the quality of representation of rows/columnsfviz_cos2
Enhanced Visualization of Dendrogramfviz_dend
Draw confidence ellipses around the categoriesfviz_ellipses
Visualize Factor Analysis of Mixed Datafviz_famd fviz_famd_ind fviz_famd_var
Visualize Hierarchical Multiple Factor Analysisfviz_hmfa fviz_hmfa_ind fviz_hmfa_quali_biplot fviz_hmfa_var
Visualize Multiple Correspondence Analysisfviz_mca fviz_mca_biplot fviz_mca_ind fviz_mca_var
Plot Model-Based Clustering Results using ggplot2fviz_mclust fviz_mclust_bic
Visualize Multiple Factor Analysisfviz_mfa fviz_mfa_axes fviz_mfa_ind fviz_mfa_quali_biplot fviz_mfa_var
Dertermining and Visualizing the Optimal Number of Clustersfviz_gap_stat fviz_nbclust
Visualize Principal Component Analysisfviz_pca fviz_pca_biplot fviz_pca_ind fviz_pca_var
Visualize Silhouette Information from Clusteringfviz_silhouette
Extract the results for rows/columns - CAget_ca get_ca_col get_ca_row
Assessing Clustering Tendencyget_clust_tendency
Extract the results for individuals and variables - FAMDget_famd get_famd_ind get_famd_var
Extract the results for individuals/variables/group/partial axes - HMFAget_hmfa get_hmfa_ind get_hmfa_partial get_hmfa_var
Extract the results for individuals/variables - MCAget_mca get_mca_ind get_mca_var
Extract the results for individuals/variables/group/partial axes - MFAget_mfa get_mfa_ind get_mfa_partial_axes get_mfa_var
Extract the results for individuals/variables - PCAget_pca get_pca_ind get_pca_var
Computes Hierarchical Clustering and Cut the Treehcut
Hierarchical k-means clusteringhkmeans hkmeans_tree print.hkmeans
House tasks contingency tablehousetasks
A dataset containing clusters of multiple shapesmultishapes
Poisonpoison
Print method for an object of class factoextraprint.factoextra