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 [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]
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]
Its syntax has been referred to as "supremely readable". [12] 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. [13] [14] On the other hand, some [15] have argued that tidyverse is a very effective way to introduce complete beginners to programming, as pedagogically it allows students to quickly begin doing powerful data processing tasks. [16] [15] Further to this, some practitioners have pointed out that data processing tasks are intuitively much easier to chain together with tidyverse compared to Python Pandas. [17]
The core packages, which provide functionality to model, transform, and visualize data, include: [18]
Additional packages assist the core collection. [19] Other packages based on the tidy data principles are regularly developed, such as tidytext [20] for text analysis, tidymodels [21] for machine learning, or tidyquant [22] for financial operations.
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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 [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]
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]
Its syntax has been referred to as "supremely readable". [12] 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. [13] [14] On the other hand, some [15] have argued that tidyverse is a very effective way to introduce complete beginners to programming, as pedagogically it allows students to quickly begin doing powerful data processing tasks. [16] [15] Further to this, some practitioners have pointed out that data processing tasks are intuitively much easier to chain together with tidyverse compared to Python Pandas. [17]
The core packages, which provide functionality to model, transform, and visualize data, include: [18]
Additional packages assist the core collection. [19] Other packages based on the tidy data principles are regularly developed, such as tidytext [20] for text analysis, tidymodels [21] for machine learning, or tidyquant [22] for financial operations.
{{
cite book}}
: CS1 maint: location missing publisher (
link)
{{
cite book}}
: CS1 maint: location missing publisher (
link) CS1 maint: multiple names: authors list (
link)
{{
cite book}}
: CS1 maint: location missing publisher (
link)