Extract and Visualize the Results of Multivariate Data Analyses
Deprecated Functions
Enhanced Distance Matrix Computation and Visualization
Visual enhancement of clustering analysis
Extract and visualize the eigenvalues/variances of dimensions
Subset and summarize the output of factor analyses
Visualizing Multivariate Analyse Outputs
Add supplementary data to a plot
Visualize Correspondence Analysis
Visualize Clustering Results
Visualize the contributions of row/column elements
Visualize the quality of representation of rows/columns
Enhanced Visualization of Dendrogram
Draw confidence ellipses around the categories
Visualize Factor Analysis of Mixed Data
Visualize Hierarchical Multiple Factor Analysis
Visualize Multiple Correspondence Analysis
Plot Model-Based Clustering Results using ggplot2
Visualize Multiple Factor Analysis
Dertermining and Visualizing the Optimal Number of Clusters
Visualize Principal Component Analysis
Visualize Silhouette Information from Clustering
Extract the results for rows/columns - CA
Assessing Clustering Tendency
Extract the results for individuals and variables - FAMD
Extract the results for individuals/variables/group/partial axes - HMF...
Extract the results for individuals/variables - MCA
Extract the results for individuals/variables/group/partial axes - MFA
Extract the results for individuals/variables - PCA
Computes Hierarchical Clustering and Cut the Tree
Hierarchical k-means clustering
Print method for an object of class factoextra
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.
Useful links