May 1, 2024
3 minute read
R packages are a fundamental part of the R programming language. They allow users to extend the functionality of R by adding new functions, data structures, and other objects. R packages are created and shared by the R community, and there are thousands of packages available on the Comprehensive R Archive Network (CRAN).
Learning about R packages can be beneficial for a variety of reasons. First, it allows you to use the work of others to extend the functionality of R. This can save you time and effort, and it can also help you to learn from the experience of others.
Second, learning about R packages can help you to understand how R works. By seeing how others have created packages, you can learn about the structure of R code and the best practices for package development.
Third, learning about R packages can help you to develop your own packages. This can be a valuable skill for researchers, data scientists, and other professionals who need to share their work with others.
There are many ways to learn about R packages. You can read books, articles, and blog posts about R packages. You can also take online courses or workshops about R packages. The online courses listed below will help you learn about the fundamentals of R packages.
kl7kff|
Find a path to becoming a R Packages. Learn more at:
OpenCourser.com/topic/kl7kff/r
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
R Packages.
Provides a comprehensive overview of R packages, covering everything from creating and sharing packages to using packages in your own work.
Provides a comprehensive overview of the tidyverse, a collection of R packages for data science.
Provides a comprehensive overview of R, covering everything from the basics of the language to advanced topics such as statistical modeling and machine learning.
Provides a detailed guide to using bookdown, an R package for creating books and technical documents in R Markdown.
Provides a detailed guide to advanced R programming, covering topics such as functional programming, data manipulation, and statistical modeling.
Provides a detailed guide to writing R extensions, which are C, C++, or Fortran code that can be used to extend the functionality of R.
Provides a detailed guide to using ggplot2, an R package for creating ggplot2 graphics.
Provides a detailed guide to using R Markdown, a tool for creating dynamic, reproducible reports in R.
Provides a detailed guide to using knitr, an R package for creating dynamic, reproducible reports.
Provides a practical introduction to R programming, covering everything from data manipulation and visualization to statistical modeling.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/kl7kff/r
Save
