Package: ggfacto 0.4.0

ggfacto: Graphs for Correspondence Analysis

Readable, complete and pretty graphs for multiple correspondence analysis, correspondence analysis and principal component analysis made with 'FactoMineR'. They can be rendered as interactive 'HTML' plots, showing useful information at mouse hover. The interest is not mainly visual but statistical. It helps the reader to keep in mind the data contained in the cross-table or Burt table while reading the correspondence analysis, thus preventing over-interpretation. Most graphs are made with 'ggplot2', which means that you can use the + syntax to manually add as many graphical pieces you want, or change theme elements. 3D graphs are made with 'plotly'.

Authors:Brice Nocenti [aut, cre], Francois Husson [ctb, cph], Guillaume Le Ray [ctb, cph], Quentin Molto [ctb, cph]

ggfacto_0.4.0.tar.gz
ggfacto_0.4.0.zip(r-4.7-any)ggfacto_0.4.0.zip(r-4.6-any)ggfacto_0.4.0.zip(r-4.5-any)
ggfacto_0.4.0.tgz(r-4.6-any)ggfacto_0.4.0.tgz(r-4.5-any)
ggfacto_0.4.0.tar.gz(r-4.7-any)ggfacto_0.4.0.tar.gz(r-4.6-any)
ggfacto_0.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ggfacto/json (API)

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

Bug tracker:https://github.com/bricenocenti/ggfacto/issues

Pkgdown/docs site:https://bricenocenti.github.io

On CRAN:

Conda:

3.30 score 2 stars 265 downloads 34 exports 124 dependencies

Last updated from:e67bd0606b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK318
source / vignettesOK286
linux-releaseOK313
macos-releaseOK199
macos-oldrelOK183
windows-develOK225
windows-releaseOK250
windows-oldrelOK212
wasm-releaseOK160

Exports:%>%axis_coordbenzecri_mrvclust_tabcorrespondence_analysiseigenvaluesggcaggfactoggiggmcaggmca_3dggmca_dataggmca_initial_dimsggmca_plotggmca_with_base_refggpcaggpca_3dggpca_cor_circleggsave2HCPC_tabhierarchical_clustinterpretis_in_analysismaterial_colors_darkmaterial_colors_lightmca_interpretMCA2mean_sd_tabmultiple_correspondence_analysisname_axespca_interpretPCA2principal_component_analysistheme_facto

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacliclustercolorspacecowplotcpp11crosstalkdata.tableDBIDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluateFactoMineRfarverfastclusterfastmapflashClustfontawesomefontBitstreamVerafontLiberationfontquiverforcatsforecastFormulafracdifffsgdtoolsgenericsggiraphggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetsirlbaisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamitoolsmodelrmultcompViewmvtnormnlmenloptrnnetnumDerivotelpbkrtestpillarpkgconfigpromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownS7sassscalesscatterplot3dshowtextshowtextdbSparseMstringistringrsurveysurvivalsysfontssystemfontstabxplortibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisLitewithrxfunyamlzoo

Readme and manuals

Help Manual

Help pageTopics
Coordinates of the Individuals on the Axes of an Analysisaxis_coord
Benzecri's modified rate of variancebenzecri_mrv
Describe Clusters with One Tableclust_tab
Correspondence Analysis of a Crosstabcorrespondence_analysis
The Eigenvalues of an Analysiseigenvalues
Readable and Interactive Graph for Simple Correspondence Analysisggca
The Graph of an Analysisggfacto
Graphs knitted at their own aspect ratioggfacto_plot
The interpretation tables, and how they printggfacto_summary print.ggfacto_summary
Widgets written to their own fileggfacto_widget
Make a graph interactiveggi
Readable and Interactive graph for multiple correspondence analysisggmca ggmca_data ggmca_plot
Interactive 3D Plot for Multiple Correspondence Analyses (plotly::)ggmca_3d
Plot Initial Dimensions (Active Variables) of Multiple Correspondence Analysisggmca_initial_dims
Plot Initial Dimensions (Active Variables) on a Multiple Correspondence Analysesggmca_with_base_ref
Readable and Interactive Graph of the Individuals of a Principal Component Analysisggpca
Interactive 3D Plot for Principal Component Analyses (plotly::)ggpca_3d
Correlation Circle Plot for Principal Component Analysisggpca_cor_circle
Save a plot as imageggsave2
Hierarchical Clustering on the Axes of an Analysishierarchical_clust
Interpret the Axes of an Analysisinterpret mca_interpret pca_interpret
Which Rows an Analysis Was Made Onis_in_analysis
Dark Material palette for MCA level namesmaterial_colors_dark
Light Material palette for MCA pointsmaterial_colors_light
Simple Mean and SD Summary (deprecated)mean_sd_tab
Multiple Correspondence AnalysisMCA2 multiple_correspondence_analysis
Name the Axes of an Analysisname_axes
Principal Component AnalysisPCA2 principal_component_analysis
A ggplot2 Theme for Geometrical Data Analysistheme_facto