## Main functions in the factoextra package

See the online documentation (http://www.sthda.com/english/rpkgs/factoextra) for a complete list.

### Visualizing dimension reduction analysis outputs

Functions | Description |
---|---|

fviz_eig (or fviz_eigenvalue) |
Extract and visualize the eigenvalues/variances of dimensions. |

fviz_pca |
Graph of individuals/variables from the output of Principal Component Analysis (PCA). |

fviz_ca |
Graph of column/row variables from the output of Correspondence Analysis (CA). |

fviz_mca |
Graph of individuals/variables from the output of Multiple Correspondence Analysis (MCA). |

fviz_mfa |
Graph of individuals/variables from the output of Multiple Factor Analysis (MFA). |

fviz_famd |
Graph of individuals/variables from the output of Factor Analysis of Mixed Data (FAMD). |

fviz_hmfa |
Graph of individuals/variables from the output of Hierarchical Multiple Factor Analysis (HMFA). |

fviz_ellipses |
Draw confidence ellipses around the categories. |

fviz_cos2 |
Visualize the quality of representation of the row/column variable from the results of PCA, CA, MCA functions. |

fviz_contrib |
Visualize the contributions of row/column elements from the results of PCA, CA, MCA functions. |

### Extracting data from dimension reduction analysis outputs

Functions | Description |
---|---|

get_eigenvalue |
Extract and visualize the eigenvalues/variances of dimensions. |

get_pca |
Extract all the results (coordinates, squared cosine, contributions) for the active individuals/variables from Principal Component Analysis (PCA) outputs. |

get_ca |
Extract all the results (coordinates, squared cosine, contributions) for the active column/row variables from Correspondence Analysis outputs. |

get_mca |
Extract results from Multiple Correspondence Analysis outputs. |

get_mfa |
Extract results from Multiple Factor Analysis outputs. |

get_famd |
Extract results from Factor Analysis of Mixed Data outputs. |

get_hmfa |
Extract results from Hierarchical Multiple Factor Analysis outputs. |

facto_summarize |
Subset and summarize the output of factor analyses. |

### Clustering analysis and visualization

Functions | Description |
---|---|

dist(fviz_dist, get_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_mclust |
Visualize Model-based Clustering Results |

fviz_silhouette |
Visualize Silhouette Information from Clustering. |

hcut |
Computes Hierarchical Clustering and Cut the Tree |

hkmeans (hkmeans_tree, print.hkmeans) |
Hierarchical k-means clustering. |

eclust |
Visual enhancement of clustering analysis |