Building R Packages
Description
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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.
Created by: Joh…Frequently asked questions
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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan .
- Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
- Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.
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.
Created by: Johns Hopkins University-
Taught by: Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health -
Taught by: Brooke Anderson, Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University
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Johns Hopkins University The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.Syllabus
WEEK 1
Getting Started with R Packages
1 video, 16 readings expand
- Video: Welcome to Building R Packages
- Reading: Before You Start
- Reading: Using Mac OS
- Reading: Using Windows
- Reading: Using Unix/Linux
- Reading: R packages
- Reading: Basic Structure of an R Package
- Reading: DESCRIPTION File
- Reading: NAMESPACE File
- Reading: Namespace Function Notation
- Reading: Loading and Attaching a Package Namespace
- Reading: The R Sub-directory
- Reading: The man Sub-directory
- Reading: Summary
- Reading: The devtools package
- Reading: Creating a Package
- Reading: Other Functions
Graded: R Package and devtools
WEEK 2
Documentation and Testing
14 readings expand
- Reading: Documentation
- Reading: Vignette's and README Files
- Reading: Knitr / Markdown
- Reading: Common knitr Options
- Reading: Help Files and roxygen2
- Reading: Common roxygen2 Tags
- Reading: Overview
- Reading: Data for Demos
- Reading: Internal Data
- Reading: Data Packages
- Reading: Summary
- Reading: Introduction
- Reading: The testthat Package
- Reading: Passing CRAN Checks
Graded: Documenting Code
WEEK 3
Licensing, Version Control, and Software Design
25 readings expand
- Reading: Overview
- Reading: The General Public License
- Reading: The MIT License
- Reading: The CC0 License
- Reading: Overview
- Reading: Paying it Forward
- Reading: Linus’s Law
- Reading: Hiring
- Reading: Summary
- Reading: Introduction
- Reading: git
- Reading: Initializing a git repository
- Reading: Committing
- Reading: Browsing History
- Reading: Linking local repo to GitHub repo
- Reading: Syncing RStudio and GitHub
- Reading: Issues
- Reading: Pull Request
- Reading: Merge Conflicts
- Reading: Introduction
- Reading: The Unix Philosophy
- Reading: Default Values
- Reading: Naming Things
- Reading: Playing Well With Others
- Reading: Summary
Graded: Testing, GitHub, and Open Source
WEEK 4
Continuous Integration and Cross Platform Development
13 readings expand
- Reading: Overview
- Reading: Web Services for Continuous Integration
- Reading: Using Travis
- Reading: Using AppVeyor
- Reading: Summary
- Reading: Introduction
- Reading: Handling Paths
- Reading: Saving Files & rappdirs
- Reading: rappdirs
- Reading: Options and Starting R
- Reading: Package Installation
- Reading: Environmental Attributes
- Reading: Summary
Graded: Building an R Package
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