Package Directives and Collaboration Networks in CRAN

Core visualizations and summaries for the CRAN package database. The package provides comprehensive methods for cleaning up and organizing the information in the CRAN package database, for building package directives networks (depends, imports, suggests, enhances, linking to) and collaboration networks, producing package dependence trees, and for computing useful summaries and producing interactive visualizations from the resulting networks and summaries. The resulting networks can be coerced to 'igraph' <> objects for further analyses and modelling.


cranly 0.3

Bug fixes

  • Fixed a minor bug that may return duplicated base packages

Other improvements, updates and addition

  • Improved vignettes and fixed check erorrs that resulted in archiving on 2019-01-23
  • Improved documentsation
  • Removed testthat from Suggests in DESCRIPTION

cranly 0.2

Bug fixes

  • handling of duplicated packages in clean_CRAN_db
  • various regex improvements
  • Better handling of packages with . in their names

New functionality

  • clean_CRAN_db now accepts the matrix from available.packages
  • new extractors for cranly_network objects: suggests, depends, linking_to, imports
  • compute_dependence_tree is a recursion to compute all generations of a package (i.e. what else is installed)
  • build_dependence_tree and a plot method for extracting the dependence tree of a package
  • summary method for cranly_dependence_tree tree objects, reporting package dependence index, parents and depth

Other improvements, updates and addition

  • Added support for LinkingTo (thanks to Dirk Eddelbuettel for raising the issue)
  • Added acknowledgement to Turing Institute
  • plot methods return legend and title by default

cranly 0.1

  • First public release

Reference manual

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0.5.4 by Ioannis Kosmidis, 2 years ago

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Browse source code at

Authors: Ioannis Kosmidis [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Imports visNetwork, colorspace, igraph, magrittr, stringr, ggplot2, countrycode, wordcloud, tm

Suggests knitr, rmarkdown

Suggested by RWsearch.

See at CRAN