Package index • factoextra

Visualizing Dimension Reduction Analysis Outputs

Visualization of PCA, CA, MCA, FAMD, MFA and HMFA.

get_eig() get_eigenvalue() fviz_eig() fviz_screeplot(): Extract and visualize the eigenvalues/variances of dimensions
fviz_pca() fviz_pca_ind() fviz_pca_var() fviz_pca_biplot(): Visualize Principal Component Analysis
fviz_ca_row() fviz_ca_col() fviz_ca_biplot() fviz_ca(): Visualize Correspondence Analysis
fviz_mca_ind() fviz_mca_var() fviz_mca_biplot() fviz_mca(): Visualize Multiple Correspondence Analysis
fviz_famd_ind() fviz_famd_var() fviz_famd(): Visualize Factor Analysis of Mixed Data
fviz_mfa_ind() fviz_mfa_quali_biplot() fviz_mfa_var() fviz_mfa_axes() fviz_mfa(): Visualize Multiple Factor Analysis
fviz_hmfa_ind() fviz_hmfa_var() fviz_hmfa_quali_biplot() fviz_hmfa(): Visualize Hierarchical Multiple Factor Analysis
fviz(): Visualizing Multivariate Analysis Outputs
fviz_ellipses(): Draw confidence ellipses around the categories
fviz_cos2(): Visualize the quality of representation of rows/columns
fviz_contrib() fviz_pca_contrib(): Visualize the contributions of row/column elements

Scatter plots of UMAP / t-SNE embeddings (no eigenvalues; see the two-track note in ?fviz_umap).

Extracting data from the output of PCA, CA, MCA, FAMD, MFA and HMFA.

as_factoextra_pca(): Build a factoextra-ready object from pre-computed coordinates
facto_summarize(): Subset and summarize the output of factor analyses
get_pca() get_pca_ind() get_pca_var(): Extract the results for individuals/variables - PCA
get_ca() get_ca_col() get_ca_row(): Extract the results for rows/columns - CA
get_mca() get_mca_var() get_mca_ind(): Extract the results for individuals/variables - MCA
get_famd() get_famd_ind() get_famd_var(): Extract the results for individuals and variables - FAMD
get_mfa() get_mfa_ind() get_mfa_var() get_mfa_partial_axes(): Extract the results for individuals/variables/group/partial axes - MFA
get_hmfa() get_hmfa_ind() get_hmfa_var() get_hmfa_partial(): Extract the results for individuals/variables/group/partial axes - HMFA

Computing and visualizing clustering

get_dist() fviz_dist(): Enhanced Distance Matrix Computation and Visualization
get_clust_tendency(): Assessing Clustering Tendency
fviz_nbclust() fviz_gap_stat(): Determining and Visualizing the Optimal Number of Clusters
fviz_dend(): Enhanced Visualization of Dendrogram
fviz_cluster(): Visualize Clustering Results
fviz_silhouette(): Visualize Silhouette Information from Clustering
hcut(): Computes Hierarchical Clustering and Cut the Tree
hkmeans() print(<hkmeans>) hkmeans_tree(): Hierarchical k-means clustering
eclust(): Visual enhancement of clustering analysis
fviz_mclust() fviz_mclust_bic(): Plot Model-Based Clustering Results using ggplot2

Data sets included in factoextra and used in examples.

Stateless, explicit helpers for publication-grade appearance.

fviz_add(): Add supplementary data to a plot
print(<factoextra>): Print method for an object of class factoextra
factominer_category_map(): Map FactoMineR category labels to legacy naming patterns
map_factominer_legacy_names(): Map legacy FactoMineR category names to current labels
get_mfa_quanti_var() get_mfa_quali_var() get_mfa_group() fviz_mfa_ind_starplot() fviz_mfa_group() fviz_mfa_quanti_var() fviz_mfa_quali_var() get_hmfa_quanti_var() get_hmfa_quali_var() get_hmfa_group() fviz_hmfa_quanti_var() fviz_hmfa_quali_var() fviz_hmfa_ind_starplot() fviz_hmfa_group(): Deprecated Functions