The tidyverse is a collection of

open source Open source is source code that is made freely available for possible modification and redistribution. Products include permission to use the source code, design documents, or content of the product. The open-source model is a decentralized sof ...

packages for the

R programming language R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinforma ...

introduced by Hadley Wickham and his team that "share an underlying design philosophy, grammar, and data structures" of tidy data. Characteristic features of tidyverse packages include extensive use of non-standard evaluation and encouraging

piping Within industry, piping is a system of pipes used to convey fluids (liquids and gases) from one location to another. The engineering discipline of piping design studies the efficient transport of fluid. Industrial process piping (and accomp ...

. As of November 2018, the tidyverse package and some of its individual packages comprise 5 out of the top 10 most downloaded R packages. The tidyverse is the subject of multiple books and papers. In 2019, the ecosystem has been published in the

Journal of Open Source Software The ''Journal of Open Source Software'' is a peer-reviewed open-access scientific journal covering open-source software from any research discipline. The journal was founded in 2016 by editors Arfon Smith, Kyle Niemeyer, Dan Katz, Kevin Moerman, an ...

. 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. 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.

Packages

The core packages, which provide functionality to model, transform, and visualize data, include: * ggplot2 * dplyr * ''tidyr'' * ''readr'' * ''purrr'' * ''tibble'' * ''stringr'' * ''forcats'' Additional packages assist the core collection. There is also a constantly growing gamut of useful packages available, based on the tidy data principles, such a
tidytext
for text analysis
tidymodels
for machine learning, o
tidyquant
for financial operations, just to name a few.

References

{{R (programming language) Data analysis software Statistical software Free R (programming language) software