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.


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.

Install the latest version from GitHub

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

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

News

factoextra 1.0.3

  • New fviz_mfa function to plot MFA individuals, partial individuals, quantitive variables, categorical variables, groups relationship square and partial axes (@inventionate, #4).

  • New fviz_hmfa function to plot HMFA individuals, quantitive variables, categorical variables and groups relationship square (@inventionate, #4).

  • New get_mfa and get_hmfa function (@inventionate, #4).

  • fviz_ca, fviz_pca, fviz_mca, fviz_mfa and fviz_hmfa ggrepel support (@inventionate, #4).

  • Updated fviz_summarize, eigenvalue, fviz_contrib and fviz_cos2 functions, to compute FactoMineR MFA and HMFA results (@inventionate, #4).

  • fviz_cluster() added. This function can be used to visualize the outputs of clustering methods including: kmeans() [stats package]; pam(), clara(), fanny() [cluster package]; dbscan() [fpc package]; Mclust() [mclust package]; HCPC() [FactoMineR package]; hkmeans() [factoextra].

  • fviz_silhouette() added. Draws the result of cluster silhouette analyses computed using the function silhouette()[cluster package]

  • fviz_nbclust(): Dertemines and visualize the optimal number of clusters

  • fviz_gap_stat(): Visualize the gap statistic generated by the function clusGap() [in cluster package]

  • hcut(): Computes hierarchical clustering and cut the tree into k clusters.

  • hkmeans(): Hierarchical k-means clustering. Hybrid approach to avoid the initial random selection of cluster centers.

  • get_clust_tendency(): Assessing clustering tendency

  • fviz_dend(): Enhanced visualization of dendrogram

  • eclust(): Visual enhancement of clustering analysis

  • get_dist() and fviz_dist(): Enhanced Distance Matrix Computation and Visualization

  • eclust(): Visual enhancement of clustering analysis

  • Require R >= 3.1.0
  • A dataset named "multishapes" has been added. It contains clusters of multiple shapes. Useful for comparing density-based clustering and partitioning methods such as k-means
  • The argument jitter is added to the functions fviz_pca(), fviz_mca() and fviz_ca() and fviz_cluster() in order to reduce overplotting of points and texts
  • The functions fviz_*() now use ggplot2::stat_ellipse() for drawing ellipses.
  • Unknown parameters "shape" removed from geom_text (@bdboy, #5)

factoextra 1.0.2

  • Visualization of Correspondence Analysis outputs from different R packages (FactoMineR, ca, ade4, MASS)
  • fviz_ca_row()
  • fviz_ca_col()
  • fviz_ca_biplot()
  • Extract results from CA output
  • get_ca_row()
  • get_ca_col()
  • get_ca()
  • Visualize the cos2 and the contributions of rows/columns. The functions can handle the output of PCA, CA and MCA
  • fviz_cos2()
  • fviz_contrib()
  • Sumarize the results of PCA, CA, MCA
  • facto_summarize()
  • fviz_pca_contrib() is dreprecated -> use fviz_contrib()
  • fviz_add: "text" are included in the allowed values for the argument geom
  • fviz_screeplot: the X parameter can be also an object of class ca [ca], coa [ade4], correspondence [MASS]
  • get_eigenvalue: X parameters and description changed
  • get_pca_ind: the argument data are no longer required

factoextra 1.0.1

  • Easy to use functions to extract and visualize the output of principal component analysis.

Reference manual

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install.packages("factoextra")

1.0.5 by Alboukadel Kassambara, a month ago


http://www.sthda.com/english/rpkgs/factoextra


Report a bug at https://github.com/kassambara/factoextra/issues


Browse source code at https://github.com/cran/factoextra


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


Documentation:   PDF Manual  


GPL-2 license


Imports abind, cluster, dendextend, FactoMineR, ggpubr, grid, stats, reshape2, ggrepel, tidyr

Depends on ggplot2

Suggests ade4, ca, igraph, MASS, knitr, mclust


Imported by CINNA, SensMap, bibliometrix, sejmRP.

Suggested by eclust.


See at CRAN