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R packages contain code, data, and documentation in a standardised collection format that can be installed by users of R, typically via a centralised software repository such as CRAN (the Comprehensive R Archive Network). [1][2] The large number of packages available for R, and the ease of installing and using them, has been cited as a major ...
R (programming language) 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.
ggplot2 is an open-source data visualization package for the statistical programming language R.Created by Hadley Wickham in 2005, ggplot2 is an implementation of Leland Wilkinson's Grammar of Graphics—a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers. ggplot2 can serve as a replacement for the base graphics in R and contains a ...
www.bioconductor.org. Bioconductor is a free, open source and open development software project for the analysis and comprehension of genomic data generated by wet lab experiments in molecular biology. Bioconductor is based primarily on the statistical R programming language, but does contain contributions in other programming languages.
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.
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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 ...
R, C, Fortran, MPI, and ØMQ. 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 ...