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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.
R is a programming language for statistical computing and data visualization.It has been adopted in the fields of data mining, bioinformatics and data analysis. [9]The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.
In the world of open source software, the Concurrent Version System (CVS) has long been the tool of choice for version control. And rightly so. CVS itself is free software, and its non-restrictive modus operandi and support for networked operation—which allow dozens of geographically dispersed programmers to share their work—fits the ...
Software versioning is the process of assigning either unique version names or unique version numbers to unique states of computer software. Within a given version number category (e.g., major or minor), these numbers are generally assigned in increasing order and correspond to new developments in the software.
The group of packages strives to provide a cohesive collection of functions to deal with common data science tasks, including data import, cleaning, transformation and visualisation (notably with the ggplot2 package). The R Infrastructure packages [31] support coding and the development of R packages and as of 2021-05-04, Metacran [17] lists 16 ...
Source Code Control System (SCCS) is a version control system designed to track changes in source code and other text files during the development of a piece of software. This allows the user to retrieve any of the previous versions of the original source code and the changes which are stored.
The three-way merge looks for sections which are the same in only two of the three files. In this case, there are two versions of the section, and the version which is in the common ancestor "C" is discarded, while the version that differs is preserved in the output. If "A" and "B" agree, that is what appears in the output.
Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [ 2 ] [ 3 ] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...