r-novice-inflammation

Programming with R

https://github.com/swcarpentry/r-novice-inflammation

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in README
  • Academic publication links
    Links to: plos.org
  • Academic email domains
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  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.7%) to scientific vocabulary

Keywords

carpentries data-visualisation data-visualization data-wrangling english knitr lesson open-educational-resources programming r rmarkdown software-carpentry stable
Last synced: 4 months ago · JSON representation ·

Repository

Programming with R

Basic Info
Statistics
  • Stars: 167
  • Watchers: 77
  • Forks: 396
  • Open Issues: 40
  • Releases: 3
Topics
carpentries data-visualisation data-visualization data-wrangling english knitr lesson open-educational-resources programming r rmarkdown software-carpentry stable
Created about 11 years ago · Last pushed 4 months ago
Metadata Files
Readme Contributing License Code of conduct Citation Zenodo

README.md

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r-novice-inflammation

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The Carpentries teach foundational coding, and data science skills to researchers worldwide. This GitHub repository generates the Software Carpentry lesson website "Introduction to R for non-programmers using inflammation data." The lesson website can be viewed here. Making changes in this GitHub repository allows us to change the content of the lesson website.

The following people are maintainers for this lesson, and are responsible for determining which changes to incorporate into the lesson:

  • Thomas Cason (@tecason)
  • Rohit Goswami (@haozeke)
  • Hugo Gruson (@Bisaloo)
  • Katie O'Mahony (@aforestsomewhere)

Alumni:

  • Daniel Chen (@chendaniely)
  • Diya Das (@diyadas)
  • Isaac Jennings (@isaac-jennings)
  • Katrin Leinweber (@katrinleinweber)

The goal of this lesson is to teach novice programmers to write modular code to perform a data analysis. R is used to teach these skills because it is a commonly used programming language in many scientific disciplines. However, the emphasis is not on teaching every aspect of R, but instead on language agnostic principles like automation with loops and encapsulation with functions (see Best Practices for Scientific Computing to learn more). This lesson is a translation of the Python version, and is also available in MATLAB.

The example used in this lesson analyzes a set of 12 data files with inflammation data collected from a trial for a new treatment for arthritis (the data was simulated). Learners are shown how it is better to create a function and apply it to each of the 12 files using a loop instead of using copy-paste to analyze the 12 files individually.

Contributing

We value your contributions. How to contribute to this lesson is outlined in CONTRIBUTING.md. If you have questions about our contributing guidelines, please create a new issue in the issues tab and one of the maintainers will respond.

Getting Help

Please see https://github.com/carpentries/lesson-example for instructions on formatting, building, and submitting lessons, or run make in this directory for a list of helpful commands.

If you have questions or proposals, please send them to the r-discuss mailing list.

Owner

  • Name: Software Carpentry
  • Login: swcarpentry
  • Kind: organization
  • Email: team@carpentries.org

Home for Software Carpentry repos for website, lessons and templates

Citation (CITATION)

Please cite as:

John Blischak, Daniel Chen, Harriet Dashnow, and Denis Haine (eds):
"Software Carpentry: Programming with R."  Version 2016.06, June 2016,
https://github.com/swcarpentry/r-novice-inflammation,
10.5281/zenodo.57541.

GitHub Events

Total
  • Issues event: 8
  • Watch event: 5
  • Delete event: 29
  • Issue comment event: 54
  • Push event: 116
  • Pull request review event: 11
  • Pull request event: 46
  • Fork event: 8
  • Create event: 25
Last Year
  • Issues event: 8
  • Watch event: 5
  • Delete event: 29
  • Issue comment event: 54
  • Push event: 116
  • Pull request review event: 11
  • Pull request event: 46
  • Fork event: 8
  • Create event: 25

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 13
  • Total pull requests: 49
  • Average time to close issues: over 2 years
  • Average time to close pull requests: 11 days
  • Total issue authors: 11
  • Total pull request authors: 7
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.98
  • Merged pull requests: 33
  • Bot issues: 0
  • Bot pull requests: 1
Past Year
  • Issues: 5
  • Pull requests: 25
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 days
  • Issue authors: 4
  • Pull request authors: 6
  • Average comments per issue: 0.0
  • Average comments per pull request: 1.12
  • Merged pull requests: 14
  • Bot issues: 0
  • Bot pull requests: 1
Top Authors
Issue Authors
  • Bisaloo (3)
  • ndporter (1)
  • maneesha (1)
  • annajiat (1)
  • quirksahern (1)
  • worcjamessmith (1)
  • karenword (1)
  • Ammar-K (1)
  • tobyhodges (1)
  • nselem (1)
  • Helysalgado (1)
Pull Request Authors
  • carpentries-bot (26)
  • Bisaloo (17)
  • froggleston (6)
  • maneesha (4)
  • josenino95 (1)
  • github-actions[bot] (1)
  • KristinaGagalova (1)
Top Labels
Issue Labels
good first issue (1) help wanted (1)
Pull Request Labels
type: package cache (21) type: template and tools (5)

Dependencies

requirements.txt pypi
  • CommonMark *
  • PyYAML *
  • pandocfilters *
  • update-copyright *
Gemfile rubygems
  • github-pages >= 0 development
  • webrick >= 1.6.1