Package: exploreit 1.0.3

exploreit: 'SciViews::R' - Exploratory Data Analysis
Multivariate analysis and data exploration for the 'SciViews::R' dialect.
Authors:
exploreit_1.0.3.tar.gz
exploreit_1.0.3.zip(r-4.7)exploreit_1.0.3.zip(r-4.6)exploreit_1.0.3.zip(r-4.5)
exploreit_1.0.3.tgz(r-4.6-any)exploreit_1.0.3.tgz(r-4.5-any)
exploreit_1.0.3.tar.gz(r-4.7-any)exploreit_1.0.3.tar.gz(r-4.6-any)
exploreit_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
exploreit/json (API)
| # Install 'exploreit' in R: |
| install.packages('exploreit', repos = c('https://sciviews.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sciviews/exploreit/issues
Pkgdown/docs site:https://www.sciviews.org
multivariate-analysissciviewsstatistical-methods
Last updated from:1511066403. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 262 | ||
| source / vignettes | OK | 427 | ||
| linux-release-x86_64 | NOTE | 235 | ||
| macos-release-arm64 | NOTE | 217 | ||
| macos-oldrel-arm64 | NOTE | 188 | ||
| windows-devel | NOTE | 191 | ||
| windows-release | NOTE | 184 | ||
| windows-oldrel | NOTE | 203 | ||
| wasm-release | OK | 190 |
Exports:as_dissimilarityas.dissimilarityas.prcompaugmentcacircleclusterdissimilaritygeom_dendrolineglancek_meansmdsmfapcaprofile_kshepardtidy
Dependencies:abindapeaskpassbackportsbase64encbootbroombroom.mixedbslibcacachemcarcarDatachartcheckmatecliclustercodacodetoolscollapsecolorspacecommonmarkcorrplotcowplotcpp11crayoncrosstalkcurldata.tabledata.tramedeldirdendextendDerivdigestdoBydplyrDTellipseemmeansequatagsequatiomaticestimabilityevaluatefactoextraFactoMineRfarverfastclusterfastmapflashClustflextablefontawesomefontBitstreamVerafontLiberationfontquiverforcatsforecastforeignFormulafracdifffsfurrrfuturegdtoolsgenericsggdendroggfortifyggplot2ggplotifyggpubrggrepelggsciggsignifglobalsgluegridExtragridGraphicsgtablehighrHmischtmlTablehtmltoolshtmlwidgetshttpuvigraphinterpirlbaisobandjpegjquerylibjsonlitekatexknitrlabelinglaterlatticelatticeExtralazyevalleapslifecyclelistenvlme4lmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmvtnormnlmenloptrnnetnumDerivofficeropensslotelparallellypbkrtestpermutepillarpkgconfigpngpolynompromisesprotopurrrquantregR6raggrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownrpartrstatixrstudioapiS7sassscalesscatterplot3dSciViewsshinysourcetoolsSparseMstringistringrsurvivalsvBasesvFlowsyssystemfontstabularisetextshapingtibbletidyrtidyselecttimeDatetinytabletinytexurcautf8uuidV8vctrsveganviridisviridisLitewithrxfunxml2xsltxtableyamlyulab.utilszeallotzipzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| 'SciViews::R' - Exploratory Data Analysis | exploreit-package exploreit |
| Convert a dist or matrix object into a Dissimilarity object | as.dissimilarity as.dissimilarity.Dissimilarity as.dissimilarity.dist as.dissimilarity.matrix as_dissimilarity |
| Correspondence Analysis (CA) | autoplot.ca ca chart.ca |
| Draw circles in a plot | circle |
| Hierarchical Clustering Analysis | augment.Cluster autoplot.Cluster chart.Cluster cluster cluster.default cluster.dist labels.Cluster nobs.Cluster plot.Cluster predict.Cluster str.Cluster |
| Calculate a dissimilarity matrix | autoplot.Dissimilarity chart.Dissimilarity dissimilarity labels.Dissimilarity nobs.Dissimilarity print.Dissimilarity |
| Draw a line to cut a dendrogram | geom_dendroline |
| K-means clustering | augment.kmeans autoplot.k_means chart.k_means k_means plot.k_means predict.k_means profile_k |
| Multidimensional scaling or principal coordinates analysis | augment.mds autoplot.mds autoplot.shepard chart.mds chart.shepard glance.mds mds plot.mds plot.shepard shepard |
| Multiple Factor Analysis (MFA) | autoplot.MFA chart.MFA mfa |
| Principal Component Analysis (PCA) | as.prcomp as.prcomp.default as.prcomp.prcomp as.prcomp.princomp augment.princomp autoplot.pcomp chart.pcomp pca tidy.princomp |
| Scale a data frame (data.frame, data.table or tibble's tbl_df) | scale scale.data.frame scale.data.table scale.tbl_df |
