Building R Packages
- Offered byCoursera
Building R Packages at Coursera Overview
Duration | 21 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course |
Credential | Certificate |
Building R Packages at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 5 in the Mastering Software Development in R Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 21 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
Building R Packages at Coursera Course details
- 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.
Building R Packages at Coursera Curriculum
Getting Started with R Packages
Welcome to Building R Packages
Before You Start
Using Mac OS
Using Windows
Using Unix/Linux
R packages
Basic Structure of an R Package
DESCRIPTION File
NAMESPACE File
Namespace Function Notation
Loading and Attaching a Package Namespace
The R Sub-directory
The man Sub-directory
Summary
The devtools package
Creating a Package
Other Functions
R Package and devtools
Documentation and Testing
Documentation
Vignette's and README Files
Knitr / Markdown
Common knitr Options
Help Files and roxygen2
Common roxygen2 Tags
Overview
Data for Demos
Internal Data
Data Packages
Summary
Introduction
The testthat Package
Passing CRAN Checks
Licensing, Version Control, and Software Design
Overview
The General Public License
The MIT License
The CC0 License
Overview
Paying it Forward
Linus's Law
Hiring
Summary
Introduction
git
Initializing a git repository
Committing
Browsing History
Linking local repo to GitHub repo
Syncing RStudio and GitHub
Issues
Pull Request
Merge Conflicts
Introduction
The Unix Philosophy
Default Values
Naming Things
Playing Well With Others
Summary
Testing, GitHub, and Open Source
Continuous Integration and Cross Platform Development
Overview
Web Services for Continuous Integration
Using Travis
Using AppVeyor
Summary
Introduction
Handling Paths
Saving Files & rappdirs
rappdirs
Options and Starting R
Package Installation
Environmental Attributes
Summary