pkgsearch utiliza servicios web R-HUB que Munge CRAN METADATA y le permite acceder a ellos a través de varias lentes.
Instale la última versión de PKGSearch desde CRAN:
install.packages( " pkgsearch " )La versión de desarrollo está en GitHub:
pak :: pak( " r-hub/pkgsearch " )¿Necesita encontrar paquetes que resuelvan un problema particular, por ejemplo, "prueba de permutación"?
library( " pkgsearch " )
library( " pillar " ) # nicer data frame printing
pkg_search( " permutation test " ) #> - "permutation test" ----------------------------------- 2545 packages in 0.525 seconds -
#> # package version by @ title
#> 1 100 coin 1.4.3 Torsten Hothorn 7M Conditional Inference Procedures ...
#> 2 29 wPerm 1.0.1 Neil A. Weiss 8y Permutation Tests
#> 3 27 flip 2.5.0 Livio Finos 6y Multivariate Permutation Tests
#> 4 27 cpt 1.0.2 Johann Gagnon-Bartsch 5y Classification Permutation Test
#> 5 25 jmuOutlier 2.2 Steven T. Garren 5y Permutation Tests for Nonparametr...
#> 6 25 lmPerm 2.1.0 Marco Torchiano 8y Permutation Tests for Linear Models
#> 7 25 perm 1.0.0.4 Michael P. Fay 8M Exact or Asymptotic Permutation T...
#> 8 25 AUtests 0.99 Arjun Sondhi 4y Approximate Unconditional and Per...
#> 9 24 peramo 0.1.3 Duy Nghia Pham 11M Permutation Tests for Randomizati...
#> 10 24 nptest 1.1 Nathaniel E. Helwig 1y Nonparametric Bootstrap and Permu...
PKGSearch utiliza un servicio web R-Hub y una clasificación cuidadosa que coloca paquetes populares antes de los menos utilizados.
Para la búsqueda mencionada anteriormente y otros puntos de entrada a los metadatos de CRAN, ¡puede usar el complemento PKGSearch RStudio!
Seleccione el complemento "Búsqueda de paquetes CRAN" en el menú, o comience con pkg_search_addin() .
¿Desea encontrar las dependencias que las primeras versiones de testthat que tuvieron y cuándo se lanzó cada una de estas versiones?
cran_package_history( " testthat " ) #> # A data frame: 46 × 29
#> Package Type Title Version Author Maintainer Description URL License LazyData
#> * <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 testthat Package Tools fo… 0.1 Hadle… Hadley Wi… Test_that … http… GPL true
#> 2 testthat Package Testthat… 0.1.1 Hadle… Hadley Wi… A testing … http… GPL true
#> 3 testthat Package Testthat… 0.2 Hadle… Hadley Wi… A testing … http… GPL true
#> 4 testthat Package Testthat… 0.3 Hadle… Hadley Wi… A testing … http… GPL true
#> 5 testthat Package Testthat… 0.4 Hadle… Hadley Wi… A testing … http… GPL true
#> 6 testthat Package Testthat… 0.5 Hadle… Hadley Wi… A testing … http… GPL true
#> 7 testthat Package Testthat… 0.6 Hadle… Hadley Wi… A testing … http… GPL true
#> 8 testthat Package Testthat… 0.7 Hadle… Hadley Wi… A testing … http… GPL true
#> 9 testthat Package Testthat… 0.7.1 Hadle… Hadley Wi… A testing … http… GPL true
#> 10 testthat Package Testthat… 0.8 Hadle… Hadley Wi… A testing … http… MIT + … true
#> # ℹ 36 more rows
#> # ℹ 19 more variables: Collate <chr>, Packaged <chr>, Repository <chr>,
#> # `Date/Publication` <chr>, crandb_file_date <chr>, date <chr>, dependencies <list>,
#> # NeedsCompilation <chr>, Roxygen <chr>, `Authors@R` <chr>, BugReports <chr>,
#> # RoxygenNote <chr>, VignetteBuilder <chr>, Encoding <chr>, MD5sum <chr>,
#> # `Config/testthat/edition` <chr>, `Config/testthat/parallel` <chr>,
#> # `Config/testthat/start-first` <chr>, `Config/Needs/website` <chr>
¿Quieres saber qué paquetes están en tendencia en CRAN en estos días? pkgsearch puede ayudar!
cran_trending() #> # A data frame: 100 × 2
#> package score
#> <chr> <chr>
#> 1 phonfieldwork 12003.3660589060308600
#> 2 piggyback 3533.5488580665345700
#> 3 bqror 2539.1373169766521600
#> 4 optigrab 2488.5245901639344300
#> 5 neuralGAM 2316.0993560257589700
#> 6 fido 1384.4350374470856400
#> 7 PKI 1086.1091255658803900
#> 8 gtExtras 937.5656399404342000
#> 9 toastui 830.0050684237202200
#> 10 EcoDiet 829.2880258899676400
#> # ℹ 90 more rows
cran_top_downloaded() #> # A data frame: 100 × 2
#> package count
#> <chr> <chr>
#> 1 ggplot2 402253
#> 2 rlang 388952
#> 3 lifecycle 365594
#> 4 dplyr 357313
#> 5 cli 347970
#> 6 vctrs 342368
#> 7 jsonlite 296204
#> 8 tibble 291159
#> 9 Rcpp 289254
#> 10 glue 285878
#> # ℹ 90 more rows
¿Tienes curiosidad por los últimos lanzamientos o archivales?
cran_events() #> CRAN events (events)---------------------------------------------------------------------
#> . When Package Version Title
#> + 4 hours LipidomicsR 0.3.6 Elegant Tools for Processing and Visualization of Lip...
#> + 4 hours fabletools 0.4.2 Core Tools for Packages in the 'fable' Framework
#> + 5 hours ripc 0.3.0 Download and Tidy IPC and CH Data
#> + 6 hours acled.api 1.1.8 Automated Retrieval of ACLED Conflict Event Data
#> + 6 hours memoiR 1.2-9 R Markdown and Bookdown Templates to Publish Document...
#> + 7 hours SAiVE 1.0.5 Functions Used for SAiVE Group Research, Collaboratio...
#> + 7 hours colorscience 1.0.9 Color Science Methods and Data
#> + 7 hours ieugwasr 1.0.0 Interface to the 'OpenGWAS' Database API
#> + 7 hours rococo 1.1.8 Robust Rank Correlation Coefficient and Test
#> + 10 hours BMRMM 1.0.1 An Implementation of the Bayesian Markov (Renewal) Mi...
Por defecto, devuelve un breve resumen de los diez mejores éxitos de búsqueda. Sus detalles se pueden imprimir utilizando la opción format = "long" de pkg_search() , o simplemente llamando pkg_search() nuevamente, sin ningún argumento, después de una búsqueda:
library( pkgsearch )
pkg_search( " C++ " ) #> - "C++" ----------------------------------------------- 10000 packages in 0.304 seconds -
#> # package version by @ title
#> 1 100 Rcpp 1.0.12 Dirk Eddelbuettel 3M Seamless R and C++ Integration
#> 2 30 BH 1.84.0.0 Dirk Eddelbuettel 3M Boost C++ Header Files
#> 3 19 inline 0.3.19 Dirk Eddelbuettel 3y Functions to Inline C, C++, F...
#> 4 14 SnowballC 0.7.1 Milan Bouchet-Valat 1y Snowball Stemmers Based on th...
#> 5 12 glpkAPI 1.3.4 Mihail Anton 1y R Interface to C API of GLPK
#> 6 10 RcppProgress 0.4.2 Karl Forner 4y An Interruptible Progress Bar...
#> 7 9 getopt 1.20.4 Trevor L Davis 7M C-Like 'getopt' Behavior
#> 8 8 boot 1.3.30 Alessandra R. Brazzale 2M Bootstrap Functions (Original...
#> 9 8 LiblineaR 2.10.23 Thibault Helleputte 4M Linear Predictive Models Base...
#> 10 7 lme4 1.1.35.3 Ben Bolker 6d Linear Mixed-Effects Models u...
pkg_search() #> - "C++" ----------------------------------------------- 10000 packages in 0.304 seconds -
#>
#> 1 Rcpp @ 1.0.12 Dirk Eddelbuettel, 3 months ago
#> ---------------
#> # Seamless R and C++ Integration
#> The 'Rcpp' package provides R functions as well as C++ classes which offer a
#> seamless integration of R and C++. Many R data types and objects can be mapped
#> back and forth to C++ equivalents which facilitates both writing of new code
#> as well as easier integration of third-party libraries. Documentation about
#> 'Rcpp' is provided by several vignettes included in this package, via the
#> 'Rcpp Gallery' site at <https://gallery.rcpp.org>, the paper by Eddelbuettel
#> and Francois (2011, <doi:10.18637/jss.v040.i08>), the book by Eddelbuettel
#> (2013, <doi:10.1007/978-1-4614-6868-4>) and the paper by Eddelbuettel and
#> Balamuta (2018, <doi:10.1080/00031305.2017.1375990>); see 'citation("Rcpp")'
#> for details.
#> https://www.rcpp.org
#> https://dirk.eddelbuettel.com/code/rcpp.html
#> https://github.com/RcppCore/Rcpp
#>
#> 2 BH @ 1.84.0.0 Dirk Eddelbuettel, 3 months ago
#> ---------------
#> # Boost C++ Header Files
#> Boost provides free peer-reviewed portable C++ source libraries. A large part
#> of Boost is provided as C++ template code which is resolved entirely at
#> compile-time without linking. This package aims to provide the most useful
#> subset of Boost libraries for template use among CRAN packages. By placing
#> these libraries in this package, we offer a more efficient distribution system
#> for CRAN as replication of this code in the sources of other packages is
#> avoided. As of release 1.84.0-0, the following Boost libraries are included:
#> 'accumulators' 'algorithm' 'align' 'any' 'atomic' 'beast' 'bimap' 'bind'
#> 'circular_buffer' 'compute' 'concept' 'config' 'container' 'date_time'
#> 'detail' 'dynamic_bitset' 'exception' 'flyweight' 'foreach' 'functional'
#> 'fusion' 'geometry' 'graph' 'heap' 'icl' 'integer' 'interprocess' 'intrusive'
#> 'io' 'iostreams' 'iterator' 'lambda2' 'math' 'move' 'mp11' 'mpl'
#> 'multiprecision' 'numeric' 'pending' 'phoenix' 'polygon' 'preprocessor'
#> 'process' 'propery_tree' 'qvm' 'random' 'range' 'scope_exit' 'smart_ptr'
#> 'sort' 'spirit' 'tuple' 'type_traits' 'typeof' 'unordered' 'url' 'utility'
#> 'uuid'.
#> https://github.com/eddelbuettel/bh
#> https://dirk.eddelbuettel.com/code/bh.html
#>
#> 3 inline @ 0.3.19 Dirk Eddelbuettel, 3 years ago
#> -----------------
#> # Functions to Inline C, C++, Fortran Function Calls from R
#> Functionality to dynamically define R functions and S4 methods with 'inlined'
#> C, C++ or Fortran code supporting the .C and .Call calling conventions.
#> https://github.com/eddelbuettel/inline
#> https://dirk.eddelbuettel.com/code/inline.html
#>
#> 4 SnowballC @ 0.7.1 Milan Bouchet-Valat, about a year ago
#> -------------------
#> # Snowball Stemmers Based on the C 'libstemmer' UTF-8 Library
#> An R interface to the C 'libstemmer' library that implements Porter's word
#> stemming algorithm for collapsing words to a common root to aid comparison of
#> vocabulary. Currently supported languages are Arabic, Basque, Catalan, Danish,
#> Dutch, English, Finnish, French, German, Greek, Hindi, Hungarian, Indonesian,
#> Irish, Italian, Lithuanian, Nepali, Norwegian, Portuguese, Romanian, Russian,
#> Spanish, Swedish, Tamil and Turkish.
#> https://github.com/nalimilan/R.TeMiS
#>
#> 5 glpkAPI @ 1.3.4 Mihail Anton, about a year ago
#> -----------------
#> # R Interface to C API of GLPK
#> R Interface to C API of GLPK, depends on GLPK Version >= 4.42.
#>
#> 6 RcppProgress @ 0.4.2 Karl Forner, 4 years ago
#> ----------------------
#> # An Interruptible Progress Bar with OpenMP Support for C++ in R Packages
#> Allows to display a progress bar in the R console for long running
#> computations taking place in c++ code, and support for interrupting those
#> computations even in multithreaded code, typically using OpenMP.
#> https://github.com/kforner/rcpp_progress
#>
#> 7 getopt @ 1.20.4 Trevor L Davis, 7 months ago
#> -----------------
#> # C-Like 'getopt' Behavior
#> Package designed to be used with Rscript to write '#!' shebang scripts that
#> accept short and long flags/options. Many users will prefer using instead the
#> packages optparse or argparse which add extra features like automatically
#> generated help option and usage, support for default values, positional
#> argument support, etc.
#> https://github.com/trevorld/r-getopt
#>
#> 8 boot @ 1.3.30 Alessandra R. Brazzale, 2 months ago
#> ---------------
#> # Bootstrap Functions (Originally by Angelo Canty for S)
#> Functions and datasets for bootstrapping from the book "Bootstrap Methods and
#> Their Application" by A. C. Davison and D. V. Hinkley (1997, CUP), originally
#> written by Angelo Canty for S.
#>
#> 9 LiblineaR @ 2.10.23 Thibault Helleputte, 4 months ago
#> ---------------------
#> # Linear Predictive Models Based on the LIBLINEAR C/C++ Library
#> A wrapper around the LIBLINEAR C/C++ library for machine learning (available
#> at <https://www.csie.ntu.edu.tw/~cjlin/liblinear/>). LIBLINEAR is a simple
#> library for solving large-scale regularized linear classification and
#> regression. It currently supports L2-regularized classification (such as
#> logistic regression, L2-loss linear SVM and L1-loss linear SVM) as well as
#> L1-regularized classification (such as L2-loss linear SVM and logistic
#> regression) and L2-regularized support vector regression (with L1- or
#> L2-loss). The main features of LiblineaR include multi-class classification
#> (one-vs-the rest, and Crammer & Singer method), cross validation for model
#> selection, probability estimates (logistic regression only) or weights for
#> unbalanced data. The estimation of the models is particularly fast as compared
#> to other libraries.
#> <https://dnalytics.com/software/liblinear/>
#>
#> 10 lme4 @ 1.1.35.3 Ben Bolker, 6 days ago
#> ------------------
#> # Linear Mixed-Effects Models using 'Eigen' and S4
#> Fit linear and generalized linear mixed-effects models. The models and their
#> components are represented using S4 classes and methods. The core
#> computational algorithms are implemented using the 'Eigen' C++ library for
#> numerical linear algebra and 'RcppEigen' "glue".
#> https://github.com/lme4/lme4/
La función more() se puede usar para mostrar el siguiente lote de golpes de búsqueda, los lotes contienen diez paquetes de forma predeterminada. ps() es un alias más corto para pkg_search() :
ps( " google " ) #> - "google" ---------------------------------------------- 171 packages in 0.034 seconds -
#> # package version by @ title
#> 1 100 googleVis 0.7.1 Markus Gesmann 1y R Interface to Google Charts
#> 2 44 bigQueryR 0.5.0 Mark Edmondson 5y Interface with Google BigQue...
#> 3 40 googletraffic 0.1.5 Robert Marty 3M Google Traffic
#> 4 40 rgoogleclassroom 0.9.1 Candace Savonen 9M API Wrapper for Google Class...
#> 5 36 googledrive 2.1.1 Jennifer Bryan 11M An Interface to Google Drive
#> 6 36 gcite 0.10.1 John Muschelli 5y Google Citation Parser
#> 7 36 plusser 0.4.0 Christoph Waldhauser 10y A Google+ Interface for R
#> 8 36 ganalytics 0.10.7 Johann de Boer 5y Interact with 'Google Analyt...
#> 9 36 pluscode 0.1.0 Michael Doyle 5y Encoder for Google 'Pluscodes'
#> 10 34 gargle 1.5.2 Jennifer Bryan 9M Utilities for Working with G...
more() #> - "google" ---------------------------------------------- 171 packages in 0.051 seconds -
#> # package version by @ title
#> 11 33 r4googleads 0.1.1 Johannes Burkhardt 2y 'Google Ads API' Interface
#> 12 33 adwordsR 0.3.1 Sean Longthorpe 6y Access the 'Google Adwords' API
#> 13 33 rgoogleslides 0.3.2 Hairizuan Noorazman 4y R Interface to Google Slides
#> 14 33 sparkbq 0.1.1 Martin Studer 4y Google 'BigQuery' Support for ...
#> 15 33 bigrquery 1.5.1 Hadley Wickham 1M An Interface to Google's 'BigQ...
#> 16 33 googleAuthR 2.0.1 Mark Edmondson 1y Authenticate and Create Google...
#> 17 33 googlePolylines 0.8.4 David Cooley 8M Encoding Coordinates into 'Goo...
#> 18 33 googleAnalyticsR 1.1.0 Mark Edmondson 2y Google Analytics API into R
#> 19 33 googler 0.0.1 Michael W. Kearney 5y Google from the R Console
#> 20 31 bigrquerystorage 1.1.0 Bruno Tremblay 19d An Interface to Google's 'BigQ...
El servidor de búsqueda utiliza los votos de las palabras en los metadatos indexados y la frase de búsqueda. Esto significa que el "color" y los "colores" ofrecen exactamente el mismo resultado. También lo hagan "colorante", "coloreado", etc. (a menos que uno sea un nombre exacto en el paquete o coincida con otro campo no con tallo).
ps( " colour " , size = 3 ) #> - "colour" ---------------------------------------------- 329 packages in 0.021 seconds -
#> # package version by @ title
#> 1 100 colorspace 2.1.0 Achim Zeileis 1y A Toolbox for Manipulating and Assessi...
#> 2 51 shape 1.4.6.1 Karline Soetaert 2M Functions for Plotting Graphical Shape...
#> 3 37 dichromat 2.0.0.1 Thomas Lumley 2y Color Schemes for Dichromats
ps( " colours " , size = 3 ) #> - "colours" --------------------------------------------- 327 packages in 0.018 seconds -
#> # package version by @ title
#> 1 100 colorspace 2.1.0 Achim Zeileis 1y A Toolbox for Manipulating and Assessi...
#> 2 51 shape 1.4.6.1 Karline Soetaert 2M Functions for Plotting Graphical Shape...
#> 3 37 dichromat 2.0.0.1 Thomas Lumley 2y Color Schemes for Dichromats
La característica más importante de un motor de búsqueda es la clasificación de los resultados. Los mejores resultados deben enumerarse primero. PKGSearch utiliza puntuación ponderada, donde una coincidencia en el título del paquete obtiene una puntuación más alta que una coincidencia en la descripción del paquete. También utiliza el número de dependencias inversas y el número de descargas para peso los puntajes:
ps( " colour " )[, c( " score " , " package " , " revdeps " , " downloads_last_month " )] #> # A data frame: 10 × 4
#> score package revdeps downloads_last_month
#> <dbl> <chr> <int> <int>
#> 1 6717. colorspace 71 1
#> 2 3442. shape 19 1
#> 3 2490. dichromat 7 1
#> 4 2110. RColorBrewer 130 1
#> 5 1632. crayon 3 1
#> 6 1631. colorRamps 3 1
#> 7 1546. colorizer 1 1
#> 8 1496. munsell 3 1
#> 9 1463. colouR 1 1
#> 10 1457. plotrix 62 1
El motor de búsqueda prefiere que coincidan las frases completas sobre palabras individuales. Por ejemplo, la frase de búsqueda "Prueba de permutación" clasificará la moneda más alta que la prueba, aunque la prueba es un resultado mucho mejor para la "prueba" de una sola palabra. (De hecho, al momento de la escritura, la prueba no está ni siquiera en la primera página de resultados).
ps( " permutation test " ) #> - "permutation test" ----------------------------------- 2545 packages in 0.048 seconds -
#> # package version by @ title
#> 1 100 coin 1.4.3 Torsten Hothorn 7M Conditional Inference Procedures ...
#> 2 29 wPerm 1.0.1 Neil A. Weiss 8y Permutation Tests
#> 3 27 flip 2.5.0 Livio Finos 6y Multivariate Permutation Tests
#> 4 27 cpt 1.0.2 Johann Gagnon-Bartsch 5y Classification Permutation Test
#> 5 25 jmuOutlier 2.2 Steven T. Garren 5y Permutation Tests for Nonparametr...
#> 6 25 lmPerm 2.1.0 Marco Torchiano 8y Permutation Tests for Linear Models
#> 7 25 perm 1.0.0.4 Michael P. Fay 8M Exact or Asymptotic Permutation T...
#> 8 25 AUtests 0.99 Arjun Sondhi 4y Approximate Unconditional and Per...
#> 9 24 peramo 0.1.3 Duy Nghia Pham 11M Permutation Tests for Randomizati...
#> 10 24 nptest 1.1 Nathaniel E. Helwig 1y Nonparametric Bootstrap and Permu...
Si toda la frase no coincide, PKGSearch recurre a palabras coincidentes individuales. Por ejemplo, una coincidencia de cualquiera de las palabras es suficiente aquí, para ingresar a la primera página de resultados:
ps( " test http " ) #> - "test http" ------------------------------------------ 7037 packages in 0.182 seconds -
#> # package version by @ title
#> 1 100 httptest 4.2.2 Neal Richardson 3M A Test Environment for HTTP Requests
#> 2 92 webfakes 1.3.0 Gábor Csárdi 4M Fake Web Apps for HTTP Testing
#> 3 42 psych 2.4.3 William Revelle 1M Procedures for Psychological, Psycho...
#> 4 29 testthat 3.2.1.1 Hadley Wickham 9d Unit Testing for R
#> 5 23 pipeGS 0.4 Hera He 6y Permutation p-Value Estimation for G...
#> 6 19 RCurl 1.98.1.14 CRAN Team 3M General Network (HTTP/FTP/...) Clien...
#> 7 16 httr 1.4.7 Hadley Wickham 8M Tools for Working with URLs and HTTP
#> 8 16 tseries 0.10.55 Kurt Hornik 5M Time Series Analysis and Computation...
#> 9 15 MASS 7.3.60.0.1 Brian Ripley 3M Support Functions and Datasets for V...
#> 10 14 webmockr 0.9.0 Scott Chamberlain 1y Stubbing and Setting Expectations on...
El motor de búsqueda utiliza un diccionario para asegurarse de que los metadatos y consultas del paquete dadas en inglés británico y americano produzcan los mismos resultados. Por ejemplo, tenga en cuenta la ortografía del color/color en los resultados:
ps( " colour " ) #> - "colour" ---------------------------------------------- 329 packages in 0.472 seconds -
#> # package version by @ title
#> 1 100 colorspace 2.1.0 Achim Zeileis 1y A Toolbox for Manipulating and Asse...
#> 2 51 shape 1.4.6.1 Karline Soetaert 2M Functions for Plotting Graphical Sh...
#> 3 37 dichromat 2.0.0.1 Thomas Lumley 2y Color Schemes for Dichromats
#> 4 31 RColorBrewer 1.1.3 Erich Neuwirth 2y ColorBrewer Palettes
#> 5 24 crayon 1.5.2 Gábor Csárdi 2y Colored Terminal Output
#> 6 24 colorRamps 2.3.4 Gregory Jefferis 2M Builds Color Tables
#> 7 23 colorizer 0.1.0 David Zumbach 3y Colorize Old Images Using the 'DeOl...
#> 8 22 munsell 0.5.1 Charlotte Wickham 21d Utilities for Using Munsell Colours
#> 9 22 colouR 0.1.1 Alan Inglis 7M Create Colour Palettes from Images
#> 10 22 plotrix 3.8.4 Duncan Murdoch 5M Various Plotting Functions
ps( " color " ) #> - "color" ----------------------------------------------- 328 packages in 0.028 seconds -
#> # package version by @ title
#> 1 100 colorspace 2.1.0 Achim Zeileis 1y A Toolbox for Manipulating and Asse...
#> 2 51 shape 1.4.6.1 Karline Soetaert 2M Functions for Plotting Graphical Sh...
#> 3 37 dichromat 2.0.0.1 Thomas Lumley 2y Color Schemes for Dichromats
#> 4 31 RColorBrewer 1.1.3 Erich Neuwirth 2y ColorBrewer Palettes
#> 5 24 crayon 1.5.2 Gábor Csárdi 2y Colored Terminal Output
#> 6 24 colorRamps 2.3.4 Gregory Jefferis 2M Builds Color Tables
#> 7 23 colorizer 0.1.0 David Zumbach 3y Colorize Old Images Using the 'DeOl...
#> 8 22 munsell 0.5.1 Charlotte Wickham 21d Utilities for Using Munsell Colours
#> 9 22 plotrix 3.8.4 Duncan Murdoch 5M Various Plotting Functions
#> 10 22 colouR 0.1.1 Alan Inglis 7M Create Colour Palettes from Images
Especialmente cuando se busca nombres de mantenedores de paquetes, es conveniente usar las letras ASCII correspondientes para caracteres no ASCII en frases de búsqueda. Por ejemplo, las siguientes dos consultas producen los mismos resultados. Tenga en cuenta que el caso también se ignora.
ps( " gabor " , size = 5 ) #> - "gabor" ----------------------------------------------- 105 packages in 0.017 seconds -
#> # package version by @ title
#> 1 100 zoo 1.8.12 Achim Zeileis 1y S3 Infrastructure for Regular and Irregula...
#> 2 73 lpSolve 5.6.20 Gábor Csárdi 4M Interface to 'Lp_solve' v. 5.5 to Solve Li...
#> 3 61 roxygen2 7.3.1 Hadley Wickham 3M In-Line Documentation for R
#> 4 59 rgl 1.3.1 Duncan Murdoch 2M 3D Visualization Using OpenGL
#> 5 58 igraph 2.0.3 Kirill Müller 1M Network Analysis and Visualization
ps( " Gábor " , size = 5 ) #> - "Gábor" ----------------------------------------------- 105 packages in 0.013 seconds -
#> # package version by @ title
#> 1 100 zoo 1.8.12 Achim Zeileis 1y S3 Infrastructure for Regular and Irregula...
#> 2 73 lpSolve 5.6.20 Gábor Csárdi 4M Interface to 'Lp_solve' v. 5.5 to Solve Li...
#> 3 61 roxygen2 7.3.1 Hadley Wickham 3M In-Line Documentation for R
#> 4 59 rgl 1.3.1 Duncan Murdoch 2M 3D Visualization Using OpenGL
#> 5 58 igraph 2.0.3 Kirill Müller 1M Network Analysis and Visualization
timeout : PKGSearch sigue las opciones de timeout para las solicitudes HTTP (es decir, para pkg_search() y advanced_search() . timeout es el límite para el tiempo total de la solicitud HTTP, y es en segundos. Ver ?options para obtener detalles. Ver la documentación completa.
MIT @ Gábor Csárdi, Rstudio, R Consorcio.