Dplyr

Last updated
dplyr
Original author(s) Hadley Wickham, Romain François, Lionel Henry, Kirill Müller, Davis Vaughan
Initial releaseJanuary 7, 2014;10 years ago (2014-01-07)
Stable release
1.1.0 / January 29, 2023;21 months ago (2023-01-29)
Written in R
License MIT License
Website dplyr.tidyverse.org//

dplyr is an R package whose set of functions are designed to enable dataframe (a spreadsheet-like data structure) manipulation in an intuitive, user-friendly way. It is one of the core packages of the popular tidyverse set of packages in the R programming language. [1] Data analysts typically use dplyr in order to transform existing datasets into a format better suited for some particular type of analysis, or data visualization. [2] [3]

Contents

For instance, someone seeking to analyze a large dataset may wish to only view a smaller subset of the data. Alternatively, a user may wish to rearrange the data in order to see the rows ranked by some numerical value, or even based on a combination of values from the original dataset. Functions within the dplyr package will allow a user to perform such tasks.

dplyr was launched in 2014. [4] On the dplyr web page, the package is described as "a grammar of data manipulation, providing a consistent set of verbs that help you solve the most common data manipulation challenges." [5]

The five core verbs

While dplyr actually includes several dozen functions that enable various forms of data manipulation, the package features five primary verbs or actions: [6]

Additional functions

In addition to its five main verbs, dplyr also includes several other functions that enable exploration and manipulation of dataframes. Included among these are:

Built-in datasets

The dplyr package comes with five datasets. These are: band_instruments, band_instruments2, band_members, starwars, storms.

The copyright to dplyr is held by Posit PBC, formerly RStudio PBC. dplyr was originally released under a GPL license[ citation needed ], but in 2022, Posit changed the license terms for the package to the "more permissive" MIT License. [7] The main difference between the two types of license is that the MIT license allows subsequent re-use of code within proprietary software, whereas a GPL license does not.

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References

  1. ↑ 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 (2019-11-21). "Welcome to the Tidyverse". Journal of Open Source Software. 4 (43): 1686. doi: 10.21105/joss.01686 . ISSN   2475-9066.
  2. ↑ Yadav, Rohit (2019-10-29). "Python's Pandas vs R's Tidyverse: Who Comes Out On Top?". Analytics India Magazine. Retrieved 2021-02-06.
  3. ↑ Krill, Paul (2015-06-30). "Why R? The pros and cons of the R language". InfoWorld. Retrieved 2021-02-06.
  4. ↑ "Introducing dplyr". blog.rstudio.com. 17 January 2014. Retrieved 2020-09-02.
  5. ↑ "Function reference". dplyr.tidyverse.org. Retrieved 2021-02-06.
  6. ↑ Grolemund, Garrett; Wickham, Hadley. 5 Data transformation | R for Data Science.
  7. ↑ "A Grammar of Data Manipulation". tidyverse.org. Retrieved 2023-01-14.
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