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R Packaging and New Development Features for
Building R Packages
author: Matthias Temple date: Olympic 2015Packaging: Overview Approaches
Basically two approaches:
1. Traditional approach including
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How to fill out r packaging and new
How to fill out R packaging and what you need to know
01
Start by understanding the purpose of packaging in R. Packaging refers to the process of bundling your R code, data, and documentation together to create a reusable and shareable unit. Packaging allows for easier distribution and installation of your R code, making it more accessible to others.
02
Begin by organizing your R code files. Create a designated folder for your package and divide it into specific directories such as "R" for R code, "man" for documentation, and "data" for any necessary data files.
03
Write the necessary functions and scripts for your package in the "R" directory. Each function should have a corresponding script file with the same name as the function.
04
Create a DESCRIPTION file for your package. This file contains essential information such as the package name, version, author, description, dependencies, and more. Fill in all the required fields accurately.
05
Pay attention to the NAMESPACE file. This file controls the visibility of functions, datasets, and other elements within your package. Specify which functions should be exported and which should be kept internal.
06
Include comprehensive documentation for your package. Write documentation for each function in the "man" directory using the Rd format. Ensure that each function has a description, arguments, usage examples, and any necessary references.
07
Consider including additional data files if required by your package. Place these files in the "data" directory and document them appropriately in your package documentation.
Who needs R packaging and why?
01
R packaging is essential for R programmers and developers who want to distribute their code to users, collaborators, or the wider R community. Packaging allows for easy installation and usage of R code, ensuring consistency and reproducibility.
02
Researchers and data scientists who use R can benefit from packaging their code. By packaging their work, they can share their analyses, methods, and tools with others, promoting collaborative research and reproducibility.
03
Users looking to install and use R packages from sources like CRAN (Comprehensive R Archive Network) or GitHub will need R packaging. Packaging ensures that the installation process is straightforward and that the required dependencies are automatically managed.
In conclusion, learning how to fill out R packaging and understanding its importance is crucial for R programmers, researchers, data scientists, and users who want to share, distribute, or install R code and packages effectively.
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r packaging and new refers to the process of reporting and submitting information on packaging materials used for products.
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