Building R Packages
About this course
Writing good code for data science is only part of the job. In order to maximizing the usefulness and reusability of data science software, code must be organized and distributed in a manner that adheres to community-based standards and provides a good user experience. This course covers the primary means by which R software is organized and distributed to others. We cover R package development, writing good documentation and vignettes, writing robust software, cross-platform development, continuous integration tools, and distributing packages via CRAN and GitHub. Learners will produce R packages that satisfy the criteria for submission to CRAN.
82/100
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- What the provider tells you
- 31/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- Develop R packages following community-based standards and best practices
- Write comprehensive documentation and vignettes for R packages
- Implement robust software testing and quality assurance practices
- Configure cross-platform development for R packages
- Use continuous integration tools in R package development
- Prepare and submit R packages to CRAN
- Distribute R packages via GitHub
Course objectives
- Maximize the usefulness and reusability of data science software through proper organization
- Create R packages that adhere to community standards and provide good user experience
- Produce R packages that satisfy CRAN submission criteria
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