 The tidyverse hex logo | |
| Initial release | September 15, 2016 [1] [2] |
|---|---|
| Repository | github |
| Written in | R |
| Type | Package collection |
| License | MIT |
| Website | www |
The tidyverse is a collection of open source packages for the R programming language introduced by Hadley Wickham [3] and his team that "share an underlying design philosophy, grammar, and data structures" of tidy data. [4] Characteristic features of tidyverse packages include extensive use of non-standard evaluation and encouraging piping. [5] [6] [7]
As of November 2018, the tidyverse package and some of its individual packages comprise 5 out of the top 10 most downloaded R packages. [8] The tidyverse is the subject of multiple books and papers. [9] [10] [11] [12] In 2019, the ecosystem has been published in the Journal of Open Source Software . [13]
Its syntax has been referred to as "supremely readable", [14] and some [15] have argued that tidyverse is an effective way to introduce complete beginners to programming, as pedagogically it allows students to quickly begin doing data processing tasks. [16] [15] Moreover, some practitioners have pointed out that data processing tasks are intuitively easier to chain together with tidyverse compared to Python's equivalent data processing package, pandas. [17] There is also an active R community around the tidyverse. For example, there is the TidyTuesday social data project organised by the Data Science Learning Community (DSLC), [18] where varied real-world datasets are released each week for the community to participate, share, practice, and make learning to work with data easier. [19] Critics of the tidyverse have argued it promotes tools that are harder to teach and learn than their built-in, base R equivalents and are too dissimilar to some programming languages. [20] [21]
The tidyverse principles more generally encourage and help ensure that a universe of streamlined packages, in principle, will help alleviate dependency issues and compatibility with current and future features. [22] An example of such a tidyverse principled approach is the pharmaverse, which is a collection of R packages for clinical reporting usage in pharma. [23]
