Since version 0.3, **cranly** includes functions for extracting information from `cranly_network`

objects (see `?extractor-functions`

). All extractor functions in `cranly`

try to figure out what `y`

is in the statements

`y`

is [the] `extractor-function`

a `package`

/`author`

Let’s download, clean and organize today’s CRAN database, and build the package and author directives networks

```
package_network %>% package_by("Kurt Hornik", exact = TRUE)
#> [1] "ISOcodes" "MASS" "NLP"
#> [4] "NLPutils" "OAIHarvester" "PolynomF"
#> [7] "RKEA" "RKEAjars" "ROI"
#> [10] "ROI.plugin.msbinlp" "RWeka" "RWekajars"
#> [13] "Rcplex" "Rglpk" "Rpoppler"
#> [16] "Rsymphony" "TSP" "Unicode"
#> [19] "W3CMarkupValidator" "arules" "aucm"
#> [22] "bibtex" "bindata" "cclust"
#> [25] "chron" "clue" "cluster"
#> [28] "coin" "colorspace" "cordillera"
#> [31] "ctv" "date" "dendextend"
#> [34] "digest" "e1071" "exactRankTests"
#> [37] "fortunes" "gap" "isotone"
#> [40] "kernlab" "mda" "mistr"
#> [43] "mobForest" "movMF" "mvord"
#> [46] "openNLP" "openNLPdata" "oz"
#> [49] "pandocfilters" "party" "polyclip"
#> [52] "polynom" "princurve" "qrmdata"
#> [55] "qrmtools" "relations" "seriation"
#> [58] "sets" "signal" "skmeans"
#> [61] "slam" "stablelearner" "strucchange"
#> [64] "tau" "textcat" "tm"
#> [67] "tm.plugin.mail" "topicmodels" "tseries"
#> [70] "vcd" "wordnet" "xgobi"
```

```
author_network %>% package_with("glm")
#> [1] "glmnet" "biglm" "biglmm"
#> [4] "glm2" "glmertree" "glmx"
#> [7] "cglm" "glmmTMB" "StroupGLMM"
#> [10] "glmlep" "fastglm" "bestglm"
#> [13] "glmBfp" "GLMaSPU" "glmtlp"
#> [16] "glmbb" "glmm" "AutoStepwiseGLM"
#> [19] "glmnetUtils" "glmdm" "GLMpack"
#> [22] "poisson.glm.mix" "glmmfields" "HBglm"
#> [25] "brglm" "brglm2" "plsRglm"
#> [28] "glmdisc" "GLMMadaptive" "glm.predict"
#> [31] "mbrglm" "circglmbayes" "CPMCGLM"
#> [34] "icdGLM" "misclassGLM" "hglm"
#> [37] "hglm.data" "CompGLM" "glmgraph"
#> [40] "glmpath" "GLMMRR" "glmc"
#> [43] "randomGLM" "designGLMM" "dglm"
#> [46] "GLMsData" "DGLMExtPois" "dhglm"
#> [49] "mdhglm" "parglm" "EBglmnet"
#> [52] "pglm" "glmmML" "emax.glm"
#> [55] "ezglm" "glmvsd" "lsplsGlm"
#> [58] "speedglm" "glmmEP" "geoRglm"
#> [61] "glm.deploy" "glmaag" "glmtree"
#> [64] "glmmboot" "glmmLasso" "glmmsr"
#> [67] "glmnetcr" "glmpathcr" "glmpca"
#> [70] "GlmSimulatoR" "glmulti" "HDGLM"
#> [73] "HiCglmi" "simglm" "MGLM"
#> [76] "mglmn" "MCMCglmm" "mcemGLM"
#> [79] "mcglm" "robmixglm" "mvglmmRank"
#> [82] "r2glmm" "oglmx" "QGglmm"
#> [85] "RPEGLMEN"
```

`sf`

package```
package_network %>% suggested_by("sf", exact = TRUE)
#> [1] "blob" "covr" "dplyr" "ggplot2"
#> [5] "knitr" "lwgeom" "maps" "maptools"
#> [9] "mapview" "microbenchmark" "odbc" "pillar"
#> [13] "pool" "raster" "rgdal" "rgeos"
#> [17] "rlang" "rmarkdown" "RPostgres" "RPostgreSQL"
#> [21] "RSQLite" "sp" "spatstat" "stars"
#> [25] "testthat" "tibble" "tidyr" "tmap"
#> [29] "vctrs"
package_network %>% imported_by("sf", exact = TRUE)
#> [1] "classInt" "DBI" "graphics" "grDevices" "grid"
#> [6] "magrittr" "Rcpp" "stats" "tools" "units"
#> [11] "utils"
package_network %>% enhanced_by("sf", exact = TRUE)
#> character(0)
```

`sf`

package```
package_network %>% suggesting("sf", exact = TRUE)
#> [1] "adklakedata" "arcos" "BIOMASS"
#> [4] "biscale" "c14bazAAR" "cancensus"
#> [7] "ckanr" "DeclareDesign" "echor"
#> [10] "EcoIndR" "eddi" "eRTG3D"
#> [13] "fasterize" "geohashTools" "geojson"
#> [16] "geometa" "ggformula" "ggiraph"
#> [19] "ggplot2" "googlePolylines" "GSODR"
#> [22] "gstat" "gtfsrouter" "ipumsr"
#> [25] "isoband" "janitor" "leaflet"
#> [28] "leafpop" "leri" "lutz"
#> [31] "mapdeck" "mlr" "MODIStsp"
#> [34] "mudata2" "NetLogoR" "nlaR"
#> [37] "nlgeocoder" "osmdata" "pinochet"
#> [40] "plotly" "raster" "rcartocolor"
#> [43] "rgrass7" "rmangal" "rnoaa"
#> [46] "sdcSpatial" "sociome" "SpaDES.core"
#> [49] "SpaDES.tools" "spatialreg" "spatialwidget"
#> [52] "spbabel" "spData" "stormwindmodel"
#> [55] "streamDepletr" "swmmr" "tabularaster"
#> [58] "tricolore" "USAboundaries" "weathercan"
package_network %>% importing("sf", exact = TRUE)
#> [1] "amt" "areal" "bdl"
#> [4] "bnspatial" "brazilmaps" "btb"
#> [7] "capm" "cartogram" "cartography"
#> [10] "cdcfluview" "censusxy" "compstatr"
#> [13] "concaveman" "crawl" "crimedata"
#> [16] "cyclestreets" "diffman" "dssd"
#> [19] "ebirdst" "eixport" "elevatr"
#> [22] "EmissV" "eSDM" "eurostat"
#> [25] "exactextractr" "FedData" "fingertipscharts"
#> [28] "foieGras" "gdalUtilities" "geobr"
#> [31] "geogrid" "geojsonio" "geonetwork"
#> [34] "geoviz" "ggsn" "ggspatial"
#> [37] "grainchanger" "graph4lg" "GWSDAT"
#> [40] "hydrolinks" "jpmesh" "jpndistrict"
#> [43] "kokudosuuchi" "LAGOSNE" "landsepi"
#> [46] "lconnect" "leafem" "leafpm"
#> [49] "lidR" "linemap" "link2GI"
#> [52] "lwgeom" "macleish" "mapedit"
#> [55] "mapi" "mapsapi" "mapview"
#> [58] "MODIS" "MODISTools" "moveVis"
#> [61] "ncdfgeom" "nhdplusTools" "nhdR"
#> [64] "NipponMap" "NLMR" "nlrx"
#> [67] "oceanis" "openSTARS" "Orcs"
#> [70] "osrm" "ows4R" "parlitools"
#> [73] "pct" "plotdap" "PWFSLSmoke"
#> [76] "qualmap" "quickmapr" "raceland"
#> [79] "RCzechia" "readwritesqlite" "reproducible"
#> [82] "rerddapXtracto" "rgeopat2" "rmapshaper"
#> [85] "rmapzen" "rnaturalearth" "rpostgisLT"
#> [88] "RPyGeo" "RQGIS" "Rsagacmd"
#> [91] "rSymbiota" "sabre" "sfdct"
#> [94] "slga" "SMITIDstruct" "smoothr"
#> [97] "spatialEco" "SpatialPosition" "spatialrisk"
#> [100] "stats19" "stlcsb" "stplanr"
#> [103] "sugarbag" "tanaka" "tidycensus"
#> [106] "tidyRSS" "tidytransit" "tidyUSDA"
#> [109] "tigris" "tmap" "tmaptools"
#> [112] "trackeRapp" "transformr" "trigpoints"
#> [115] "uavRmp" "vein" "velociraptr"
#> [118] "velox" "webTRISr" "windfarmGA"
package_network %>% enhancing("sf", exact = TRUE)
#> [1] "landscapemetrics" "pointdexter"
```

`sf`

package`sf`

package`data.table`

`trackeRapp`

```
trackeRapp_maintainer <- package_network %>% maintainer_of("trackeRapp", exact = TRUE)
package_network %>% email_of(trackeRapp_maintainer, exact = TRUE)
#> [1] "[email protected]"
```

```
package_network %>% email_with("warwick.ac.uk")
#> [1] "[email protected]" "[email protected]"
#> [3] "[email protected]" "[email protected]"
#> [5] "[email protected]" "[email protected]"
#> [7] "[email protected]" "[email protected]"
#> [9] "[email protected]" "[email protected]"
#> [11] "[email protected]" "[email protected]"
#> [13] "[email protected]"
```

`semnar`

package```
package_network %>% title_of("semnar", exact = TRUE)
#> [1] "Constructing and Interacting with Databases of Presentations"
package_network %>% description_of("semnar", exact = TRUE)
#> [1] "Provides methods for constructing and maintaining a database of presentations in R. The presentations are either ones that the user gives or gave or presentations at a particular event or event series. The package also provides a plot method for the interactive mapping of the presentations using 'leaflet' by grouping them according to country, city, year and other presentation attributes. The markers on the map come with popups providing presentation details (title, institution, event, links to materials and events, and so on)."
package_network %>% version_of("semnar", exact = TRUE)
#> [1] "0.7.1"
```

Since version 0.5 **cranly** provides methods to construct word clouds of either author names, package descriptions or package titles. For example, the word cloud of the descriptions of the packages maintained by me, Achim Zeileis, and Edzer Pebesma are

or the word cloud of the titles of those packages are

```
word_cloud(package_network, maintainer = "Ioannis Kosmidis", perspective = "title", exact = TRUE,
scale = c(2, 0.1), min.freq = 1)
```