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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]
In computer programming, a usage message or help message is a brief message displayed by a program that utilizes a command-line interface for execution. This message usually consists of the correct command line usage for the program and includes a list of the correct command-line arguments or options acceptable to said program.
An MS-DOS command line, illustrating parsing into command and arguments. A command-line argument or parameter is an item of information provided to a program when it is started. [23] A program can have many command-line arguments that identify sources or destinations of information, or that alter the operation of the program.
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 ...
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.
PHP uses argc as a count of arguments and argv as an array containing the values of the arguments. [ 4 ] [ 5 ] To create an array from command-line arguments in the -foo:bar format, the following might be used:
RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.