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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
|> package_by("Kurt Hornik", exact = TRUE)
package_network #> [1] "arules" "bibtex" "bindata"
#> [4] "cclust" "chron" "clue"
#> [7] "cluster" "coin" "colorspace"
#> [10] "cordillera" "ctv" "date"
#> [13] "dendextend" "digest" "e1071"
#> [16] "exactRankTests" "fortunes" "gap"
#> [19] "gsignal" "ISOcodes" "isotone"
#> [22] "kernlab" "lpSolveAPI" "MASS"
#> [25] "mda" "mistr" "movMF"
#> [28] "mvord" "nloptr" "NLP"
#> [31] "NLPclient" "NLPutils" "OAIHarvester"
#> [34] "openNLP" "openNLPdata" "opGMMassessment"
#> [37] "oz" "pandocfilters" "party"
#> [40] "polyclip" "polynom" "PolynomF"
#> [43] "princurve" "qrmdata" "qrmtools"
#> [46] "Rcplex" "relations" "Rglpk"
#> [49] "RKEA" "RKEAjars" "ROI"
#> [52] "ROI.plugin.msbinlp" "Rpoppler" "Rsymphony"
#> [55] "RWeka" "RWekajars" "seriation"
#> [58] "sets" "signal" "skmeans"
#> [61] "slam" "stablelearner" "strucchange"
#> [64] "strucchangeRcpp" "tau" "textcat"
#> [67] "textplot" "tm" "tm.plugin.mail"
#> [70] "topicmodels" "tseries" "TSP"
#> [73] "Unicode" "vcd" "W3CMarkupValidator"
#> [76] "WeightSVM" "wordnet"
|> package_by("Ioannis")
package_network #> [1] "BCT" "betareg" "brglm" "brglm2"
#> [5] "camtrapR" "detectseparation" "enrichwith" "FLR"
#> [9] "IPMbook" "MXM" "PlackettLuce" "profileModel"
#> [13] "Rfast" "trackeR" "trackeRapp" "USP"
|> package_with("glm")
author_network #> [1] "glmlep" "glmnet" "biglm" "biglmm"
#> [5] "dbglm" "glm2" "glmertree" "glmx"
#> [9] "cglm" "glmmTMB" "aglm" "StroupGLMM"
#> [13] "fastglm" "r2glmm" "bestglm" "eventglm"
#> [17] "GLMaSPU" "glmbb" "glmm" "AutoStepwiseGLM"
#> [21] "glmnetUtils" "glmvsd" "GLMpack" "poisson.glm.mix"
#> [25] "glmmfields" "HBglm" "brglm" "brglm2"
#> [29] "GLMMRR" "plsRglm" "GLMMadaptive" "BranchGLM"
#> [33] "glm.predict" "mbrglm" "CPMCGLM" "hdpGLM"
#> [37] "glmdisc" "CIS.DGLM" "SplitGLM" "icdGLM"
#> [41] "misclassGLM" "pglm" "hglm" "hglm.data"
#> [45] "RPEGLMEN" "glmpath" "GlmSimulatoR" "glmc"
#> [49] "randomGLM" "glmmEP" "dglm" "GLMsData"
#> [53] "DGLMExtPois" "dhglm" "mdhglm" "ezglm"
#> [57] "parglm" "glmmSeq" "holiglm" "glmmML"
#> [61] "MGLM" "FGLMtrunc" "gglm" "speedglm"
#> [65] "glmm.hp" "glm.deploy" "glmtlp" "GLMcat"
#> [69] "glmtree" "glme" "glmglrt" "glmmLasso"
#> [73] "glmmPen" "glmnetcr" "glmpathcr" "glmnetSE"
#> [77] "glmpca" "glmtoolbox" "glmtrans" "glmulti"
#> [81] "glmxdiag" "HDGLM" "simglm" "htmcglm"
#> [85] "mcglm" "ICglm" "mglmn" "lsplsGlm"
#> [89] "MCMCglmm" "mcemGLM" "robmixglm" "mvglmmRank"
#> [93] "oglmx" "prettyglm" "QGglmm" "stepjglm"
sf
package|> suggested_by("sf", exact = TRUE)
package_network #> [1] "blob" "covr" "dplyr" "ggplot2"
#> [5] "knitr" "lwgeom" "maps" "mapview"
#> [9] "Matrix" "microbenchmark" "odbc" "pbapply"
#> [13] "pillar" "pool" "raster" "rlang"
#> [17] "rmarkdown" "RPostgres" "RPostgreSQL" "RSQLite"
#> [21] "sp" "spatstat" "spatstat.geom" "spatstat.random"
#> [25] "spatstat.linnet" "spatstat.utils" "stars" "terra"
#> [29] "testthat" "tibble" "tidyr" "tidyselect"
#> [33] "tmap" "vctrs" "wk"
|> imported_by("sf", exact = TRUE)
package_network #> [1] "classInt" "DBI" "graphics" "grDevices" "grid" "magrittr"
#> [7] "Rcpp" "s2" "stats" "tools" "units" "utils"
|> enhanced_by("sf", exact = TRUE)
package_network #> character(0)
sf
package|> suggesting("sf", exact = TRUE)
package_network #> [1] "accessibility" "adklakedata" "AMAPVox"
#> [4] "apsimx" "argoFloats" "auk"
#> [7] "BiodiversityR" "BIOMASS" "biscale"
#> [10] "bmstdr" "BSBT" "cancensus"
#> [13] "CAST" "censusxy" "ckanr"
#> [16] "climaemet" "climatrends" "cmhc"
#> [19] "colorist" "ctmm" "dataRetrieval"
#> [22] "deckgl" "DeclareDesign" "disdat"
#> [25] "dodgr" "echelon" "echor"
#> [28] "EcoIndR" "efdm" "ENMeval"
#> [31] "eRTG3D" "eurostat" "fasterize"
#> [34] "febr" "FlickrAPI" "gdalcubes"
#> [37] "gear" "geocmeans" "geodaData"
#> [40] "geohashTools" "geojson" "geometa"
#> [43] "geomtextpath" "geos" "gfcanalysis"
#> [46] "ggblanket" "ggformula" "gghighlight"
#> [49] "gginnards" "ggiraph" "ggpattern"
#> [52] "ggplot2" "ggrastr" "googlePolylines"
#> [55] "graphhopper" "graticule" "grwat"
#> [58] "gstat" "gtfsrouter" "ipumsr"
#> [61] "isoband" "janitor" "jsonlite"
#> [64] "kdtools" "leaflet" "leaflet.extras2"
#> [67] "leri" "lutz" "mapsFinland"
#> [70] "mdsr" "metamer" "mlr"
#> [73] "mlr3spatiotempcv" "mudata2" "nlaR"
#> [76] "o2geosocial" "oce" "od"
#> [79] "onemapsgapi" "opencage" "osmdata"
#> [82] "palmid" "pinochet" "plainview"
#> [85] "plotly" "plumber" "PointedSDMs"
#> [88] "polyCub" "polylabelr" "protolite"
#> [91] "raster" "rasterVis" "rayrender"
#> [94] "rayshader" "rcartocolor" "rdhs"
#> [97] "readwritesqlite" "recogito" "regional"
#> [100] "regweight" "reproducible" "rgbif"
#> [103] "rgee" "RGENERATEPREC" "rGhanaCensus"
#> [106] "rgrass" "rgrass7" "rinat"
#> [109] "rmangal" "RtD3" "sbtools"
#> [112] "sdcSpatial" "sdmApp" "sociome"
#> [115] "soilDB" "sp" "spacetime"
#> [118] "SpaceTimeBSS" "SpaDES.tools" "SpatialBSS"
#> [121] "spbabel" "spData" "spflow"
#> [124] "spotoroo" "spsur" "swmmr"
#> [127] "terra" "tgver" "tricolore"
#> [130] "ukpolice" "unifir" "ursa"
#> [133] "USAboundaries" "waterquality" "wk"
|> importing("sf", exact = TRUE)
package_network #> [1] "abmR" "abstr" "adw"
#> [4] "amt" "aopdata" "areal"
#> [7] "ARPALData" "ascotraceR" "aurin"
#> [10] "BARIS" "basemaps" "bayesmove"
#> [13] "bbsBayes" "bcdata" "bcputility"
#> [16] "bdc" "bdl" "BIEN"
#> [19] "bigDM" "blockCV" "bluebike"
#> [22] "bnspatial" "briskaR" "btb"
#> [25] "buffeRs" "camtrapR" "capm"
#> [28] "CARBayes" "CARBayesdata" "CARBayesST"
#> [31] "card" "cartograflow" "cartogram"
#> [34] "cartogramR" "cartography" "CatastRo"
#> [37] "cdcfluview" "cdrcR" "censable"
#> [40] "chirps" "clhs" "ClimMobTools"
#> [43] "comorosmaps" "concaveman" "conleyreg"
#> [46] "ConR" "CopernicusDEM" "covid19br"
#> [49] "covid19sf" "covidcast" "crawl"
#> [52] "crimedata" "CropScapeR" "crsuggest"
#> [55] "cshapes" "cubble" "cyclestreets"
#> [58] "datazoom.amazonia" "daymetr" "Directional"
#> [61] "distanceto" "divseg" "dots"
#> [64] "dsims" "dssd" "dwp"
#> [67] "ebirdst" "edbuildmapr" "eks"
#> [70] "elevatr" "EmissV" "envirem"
#> [73] "epiR" "epm" "eSDM"
#> [76] "exactextractr" "extRatum" "FedData"
#> [79] "fgdr" "FIESTA" "FIESTAutils"
#> [82] "fisheye" "fitbitViz" "flexpolyline"
#> [85] "flightplot" "foieGras" "forestecology"
#> [88] "FORTLS" "fsr" "galah"
#> [91] "GapAnalysis" "gbm.auto" "gdalUtilities"
#> [94] "GeNetIt" "geobr" "geodimension"
#> [97] "geodiv" "geodrawr" "geofacet"
#> [100] "geofi" "geogrid" "geojsonio"
#> [103] "geoknife" "geomander" "geomaroc"
#> [106] "geometr" "geonetwork" "geostan"
#> [109] "geouy" "geoviz" "ggOceanMaps"
#> [112] "ggseg" "ggsn" "ggspatial"
#> [115] "ggVennDiagram" "giscoR" "glottospace"
#> [118] "grainchanger" "graph4lg" "GREENeR"
#> [121] "gridpattern" "gtfs2gps" "gtfstools"
#> [124] "gwavr" "GWnnegPCA" "GWpcor"
#> [127] "gwpcormapper" "GWSDAT" "h3jsr"
#> [130] "happign" "HDSpatialScan" "helsinki"
#> [133] "hereR" "himach" "hwsdr"
#> [136] "hypsoLoop" "IceSat2R" "idbr"
#> [139] "imcRtools" "IRexamples" "itsdm"
#> [142] "japanmesh" "jpgrid" "jpmesh"
#> [145] "klexdatr" "kokudosuuchi" "LAGOSNE"
#> [148] "landsepi" "latticeDensity" "layer"
#> [151] "lazysf" "lconnect" "leafem"
#> [154] "leafgl" "leafpm" "leafpop"
#> [157] "lidaRtRee" "lidR" "linemap"
#> [160] "link2GI" "LMoFit" "lwgeom"
#> [163] "macleish" "MainExistingDatasets" "mapboxapi"
#> [166] "mapchina" "mapedit" "mapi"
#> [169] "mapiso" "mapme.biodiversity" "mapping"
#> [172] "mapsapi" "mapscanner" "mapsf"
#> [175] "mapSpain" "maptiles" "mapview"
#> [178] "MazamaSpatialPlots" "meteoland" "meteospain"
#> [181] "mgwrsar" "micromapST" "mlr3spatial"
#> [184] "MODISTools" "MODIStsp" "motif"
#> [187] "moveVis" "mregions" "MTA"
#> [190] "naturaList" "ncdfgeom" "ndi"
#> [193] "NetLogoR" "netmap" "nhdplusTools"
#> [196] "nhdR" "NipponMap" "njgeo"
#> [199] "nlrx" "nominatimlite" "oceanic"
#> [202] "oceanis" "opendatatoronto" "openeo"
#> [205] "opentripplanner" "Orcs" "osmextract"
#> [208] "osrm" "otpr" "owidR"
#> [211] "ows4R" "ozmaps" "paleopop"
#> [214] "parlitools" "pct" "pgirmess"
#> [217] "PL94171" "PlanetNICFI" "plotdap"
#> [220] "plotKML" "populR" "potential"
#> [223] "pRecipe" "prisonbrief" "pspatreg"
#> [226] "PWFSLSmoke" "qualmap" "quickmapr"
#> [229] "r5r" "raceland" "rangemap"
#> [232] "rangeMapper" "rasterbc" "rasterDT"
#> [235] "rasterpic" "raytracing" "rbenvo"
#> [238] "rcage" "redist" "redistmetrics"
#> [241] "Relectoral" "remap" "rerddapXtracto"
#> [244] "rFIA" "rfishnet2" "RFmerge"
#> [247] "rgeoda" "rgeopat2" "rgugik"
#> [250] "rmapshaper" "rmapzen" "rnaturalearth"
#> [253] "rnrfa" "roads" "robis"
#> [256] "RPyGeo" "Rsagacmd" "RStoolbox"
#> [259] "rts2" "rtsVis" "RWmisc"
#> [262] "sabre" "safedata" "sandwichr"
#> [265] "SDLfilter" "secr" "seedreg"
#> [268] "segmetric" "sen2r" "sfarrow"
#> [271] "sfdct" "sfdep" "sfhotspot"
#> [274] "sfnetworks" "sftrack" "sgsR"
#> [277] "simodels" "simplevis" "sits"
#> [280] "slendr" "smartmap" "smile"
#> [283] "SMITIDstruct" "smoothr" "spacejamr"
#> [286] "spatgeom" "spatialEco" "SpatialKDE"
#> [289] "SpatialPosition" "spatialrisk" "spatialsample"
#> [292] "spectator" "spectralR" "sphet"
#> [295] "spmodel" "spnaf" "spNetwork"
#> [298] "spqdep" "SRTsim" "starsTileServer"
#> [301] "stats19" "stplanr" "stppSim"
#> [304] "sugarbag" "SUNGEO" "supercells"
#> [307] "swfscDAS" "swfscMisc" "SWMPrExtension"
#> [310] "SWTools" "synoptReg" "tanaka"
#> [313] "telemac" "terrainr" "tidycensus"
#> [316] "tidygeoRSS" "tidyterra" "tidytransit"
#> [319] "tidyUSDA" "tigris" "tilemaps"
#> [322] "tinytiger" "tmap" "tmaptools"
#> [325] "tongfen" "track2KBA" "trackeRapp"
#> [328] "transformr" "treePlotArea" "treetop"
#> [331] "trigpoints" "uavRmp" "upstartr"
#> [334] "valhallr" "valuemap" "VancouvR"
#> [337] "VARMER" "vein" "velociraptr"
#> [340] "VicmapR" "vietnameseConverter" "waywiser"
#> [343] "weed" "WEGE" "wildlifeDI"
#> [346] "zonebuilder"
|> enhancing("sf", exact = TRUE)
package_network #> [1] "landscapemetrics"
sf
package|> depending_on("sf", exact = TRUE)
package_network #> [1] "APAtree" "arcpullr" "basf" "bcmaps" "canadamaps"
#> [6] "CCAMLRGIS" "chilemapas" "ecochange" "GADMTools" "habCluster"
#> [11] "micromap" "nngeo" "prioritizr" "RCzechia" "RGISTools"
#> [16] "rLFT" "sftime" "siland" "spatialreg" "spdep"
#> [21] "spsurvey" "sspm" "stars" "starsExtra" "stcos"
#> [26] "tilegramsR" "transfR" "wdnr.gis" "wdpar" "windAC"
sf
package|> dependency_of("sf", exact = TRUE)
package_network #> [1] "methods"
|> maintained_by("Helen")
package_network #> [1] "bild" "cold" "GENLIB" "microPop" "villager"
|> maintained_by("Helen", flat = FALSE) |> dim()
package_network #> [1] 5 67
data.table
|> maintainer_of("data.table", exact = TRUE)
package_network #> [1] "Matt Dowle"
trackeRapp
<- package_network |> maintainer_of("trackeRapp", exact = TRUE)
trackeRapp_maintainer |> email_of(trackeRapp_maintainer, exact = TRUE)
package_network #> [1] "ioannis.kosmidis@warwick.ac.uk"
|> email_with("warwick.ac.uk")
package_network #> [1] "nick.parsons@warwick.ac.uk" "ioannis.kosmidis@warwick.ac.uk"
#> [3] "haotian.xu@warwick.ac.uk" "s.tavakoli@warwick.ac.uk"
#> [5] "d.selby@warwick.ac.uk" "s.stein@warwick.ac.uk"
#> [7] "Nicole.Schwitter.1@warwick.ac.uk" "tom.berrett@warwick.ac.uk"
#> [9] "a.dickerson@warwick.ac.uk" "d.firth@warwick.ac.uk"
#> [11] "michelle.kendall@warwick.ac.uk"
semnar
package|> title_of("semnar", exact = TRUE)
package_network #> character(0)
|> description_of("semnar", exact = TRUE)
package_network #> character(0)
|> version_of("semnar", exact = TRUE)
package_network #> character(0)
|> release_date_of(Inf) |>
package_network hist(breaks = 50, main = "", xlab = "date", freq = TRUE)
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 and Edzer Pebesma are
word_cloud(package_network, maintainer = "Ioannis Kosmidis", exact = TRUE, min.freq = 1)
word_cloud(package_network, maintainer = "Edzer Pebesma", exact = TRUE, min.freq = 1)
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)
word_cloud(package_network, maintainer = "Edzer Pebesma", perspective = "title", exact = TRUE,
scale = c(2, 0.1), min.freq = 1)
More complex queries can be achieved by using the extractor functions and computing the term frequencies manually. For example, the word cloud of all packages maintained by people with “warwick.ac.uk” in their email is
<- package_network |> email_with("warwick.ac.uk", flat = FALSE)
warwick_emails <- warwick_emails$package
warwick_pkgs <- package_network |> description_of(warwick_pkgs, exact = FALSE)
descriptions <- compute_term_frequency(descriptions)
term_frequency word_cloud(term_frequency, min.freq = 5)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.