Tidyverse

The tidyverse is a collection of open source packages for the R programming language introduced by Hadley Wickham[1] and his team that "share an underlying design philosophy, grammar, and data structures" of tidy data.[2] Characteristic features of tidyverse packages include extensive use of non-standard evaluation and encouraging piping.[3][4][5]

Tidyverse
Repository
Written inR
TypePackage collection
Websitewww.tidyverse.org

As of November 2018, the tidyverse package and some of its individual packages comprise 5 out of the top 10 most downloaded R packages.[6] The tidyverse is the subject of multiple books and papers.[7][8][9][10] In 2019, the ecosystem has been published in the Journal of Open Source Software.[11]

Critics of the tidyverse have argued it promotes tools that are harder to teach and learn than their base-R equivalents and are too dissimilar to other programming languages.[12][13] On the other hand, some have argued that tidyverse is a very effective way to introduce complete beginners into programming, as pedagogically it allows students to quickly begin doing powerful data processing tasks.[14]

Packages

The core packages, which provide functionality to model, transform, and visualize data, include:[15]

Additional packages assist the core collection.[16] Other packages based on the tidy data principles are regularly developed, such as tidytext[17] for text analysis, tidymodels[18] for machine learning, or tidyquant[19] for financial operations.

References
  1. "Welcome to the Tidyverse". Revolutions. Retrieved 2018-11-26.
  2. "Tidyverse". www.tidyverse.org. Retrieved 2018-11-26.
  3. Wickham, Stefan Milton Bache and Hadley (2014-11-22), magrittr: A Forward-Pipe Operator for R, retrieved 2020-04-20
  4. Wickham, Hadley. 4 Pipes | The tidyverse style guide.
  5. Wickham, Hadley (2019). Advanced R (Second ed.). Boca Raton. ISBN 978-0815384571.
  6. "RDocumentation". www.rdocumentation.org. Retrieved 2018-11-26.
  7. Duggan, Jim (2018-09-07). "Input and output data analysis for system dynamics modelling using the tidyverse libraries of R". System Dynamics Review. 34 (3): 438–461. doi:10.1002/sdr.1600. hdl:10379/15029. ISSN 0883-7066. S2CID 70005357.
  8. Chang, Winston (2013). R Graphics Cookbook. "O'Reilly Media, Inc.". ISBN 9781449316952.
  9. C., Boehmke, Bradley (2016-11-17). Data wrangling with R. Cham. ISBN 9783319455990. OCLC 964404346.
  10. Hadley, Wickham (2017). R for data science : import, tidy, transform, visualize, and model data. Grolemund, Garrett (First ed.). Sebastopol, CA. ISBN 9781491910399. OCLC 968213225.
  11. Wickham, Hadley; Averick, Mara; Bryan, Jennifer; Chang, Winston; McGowan, Lucy D'Agostino; François, Romain; Grolemund, Garrett; Hayes, Alex; Henry, Lionel; Hester, Jim; Kuhn, Max; Pedersen, Thomas Lin; Miller, Evan; Bache, Stephan Milton; Müller, Kirill; Ooms, Jeroen; Robinson, David; Seidel, Dana Paige; Spinu, Vitalie; Takahashi, Kohske; Vaughan, Davis; Wilke, Claus; Woo, Kara; Yutani, Hiroaki (21 November 2019). "Welcome to the Tidyverse". Journal of Open Source Software. 4 (43): 1686. Bibcode:2019JOSS....4.1686W. doi:10.21105/joss.01686. S2CID 214002773.
  12. Matloff, Norm (30 September 2019). "An opinionated view of the Tidyverse "dialect" of the R language". GitHub. Retrieved 28 October 2019.
  13. Muenchen, Bob (23 March 2017). "The Tidyverse Curse". r4stats.com.
  14. on, Teach the tidyverse to beginners was published. "Teach the tidyverse to beginners". Variance Explained. Retrieved 2022-07-15.
  15. "Tidyverse packages - Tidyverse". Retrieved 2018-11-26.
  16. "Tidyverse packages". www.tidyverse.org. Retrieved 2020-12-22.
  17. Silge, Julia (2023-02-01), tidytext: Text mining using tidy tools, retrieved 2023-02-03
  18. "Tidymodels". www.tidymodels.org. Retrieved 2023-02-03.
  19. "Tidy Quantitative Financial Analysis". business-science.github.io. Retrieved 2023-02-03.
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