r-day-workshop
Materials for the Manchester Universities R day tidyverse workshop
Science Score: 41.0%
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
-
○DOI references
-
○Academic publication links
-
✓Committers with academic emails
20 of 108 committers (18.5%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (11.1%) to scientific vocabulary
Keywords from Contributors
Repository
Materials for the Manchester Universities R day tidyverse workshop
Basic Info
- Host: GitHub
- Owner: UoMResearchIT
- License: other
- Language: HTML
- Default Branch: gh-pages
- Homepage: https://uomresearchit.github.io/r-day-workshop/
- Size: 33.9 MB
Statistics
- Stars: 0
- Watchers: 4
- Forks: 2
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
R for Data Analysis
An introduction to R for non-programmers using the Gapminder data and the tidyverse.
This course is based on the Software Carpentry course, and has been abridged and modified. The most substantive changes are:
- The Tidyverse is taught (the differences between, e.g.
data.framesandtibblesis included in the notes - though this is mainly for reference). - Lists are not taught
- The episode on
tidyrhas been removed, in the interests of time. - Git isn't covered (although version control is mentioned, and the learners are signposted to the Research IT's git course)
A rendered version of the course notes can be found at https://UoMResearchIT.github.io/r-tidyverse-intro/.
A rendered version of the original Software Carpentry lesson can be found at: https://swcarpentry.github.io/r-novice-gapminder,
the lesson template documentation
for instructions on formatting, building, and submitting material,
or run make in this directory for a list of helpful commands.
By default the Makefile will build the .md images using R in a Dockerised container, which contains the same packages and versions as the machines which are used for teaching. The lessons should be compatable with newer versions of the packages, but the output (most notably the tidyverse loading messages) will be different in places. To use your local installation of R, rather than the dockerised version, modify the Makefile where indicated in its comments
The remainder of this README is from the original Software Carpentry version of the lesson:
The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.
Note that this workshop focuses on the fundamentals of the programming language R, and not on statistical analysis.
A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.
Maintainers:
Owner
- Name: Research IT, University of Manchester, UK
- Login: UoMResearchIT
- Kind: organization
- Email: ITS-research@manchester.ac.uk
- Location: Manchester, UK
- Website: http://www.itservices.manchester.ac.uk/research/
- Repositories: 35
- Profile: https://github.com/UoMResearchIT
Citation (CITATION)
Please cite as: Thomas Wright and Naupaka Zimmerman (eds): "Software Carpentry: R for Reproducible Scientific Analysis." Version 2016.06, June 2016, https://github.com/swcarpentry/r-novice-gapminder, 10.5281/zenodo.57520.
GitHub Events
Total
Last Year
Committers
Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| David Mawdsley | d****y@m****k | 451 |
| Greg Wilson | g****n@s****g | 192 |
| Raniere Silva | r****e@r****m | 162 |
| Scott Ritchie | s****3@g****m | 114 |
| François Michonneau | f****u@g****m | 92 |
| Pip Griffin | p****n@g****m | 51 |
| Naupaka Zimmerman | n****a@g****m | 49 |
| Harriet Dashnow | h****w@g****m | 35 |
| Andy Boughton | a****t@g****m | 32 |
| Andy Teucher | a****r@g****m | 29 |
| Tom Wright | t****m@m****m | 28 |
| Abigail Cabunoc Mayes | a****c@g****m | 25 |
| Maxim Belkin | m****n@g****m | 23 |
| Mateusz Kuzak | m****k@g****m | 19 |
| Timothy Rice | t****e@m****u | 15 |
| Robert McDonald | r****4@g****m | 14 |
| Aaron O'Leary | a****y@g****m | 14 |
| Bill Mills | m****j@g****m | 12 |
| Gerard Capes | g****s@m****k | 12 |
| Katrin Leinweber | 9****r | 10 |
| Karl Broman | k****n@g****m | 10 |
| Remi Daigle | r****e@d****a | 10 |
| Rémi Emonet | r****i@h****m | 10 |
| Sam Penrose | s****e@m****m | 9 |
| Noel Faux | n****x@u****u | 9 |
| W. Trevor King | w****g@t****s | 9 |
| Jeffrey Oliver | j****r@e****u | 8 |
| Clare Sloggett | c****t@g****m | 8 |
| Tim Moore | t****e@u****u | 7 |
| Jeffrey Arnold | j****d@g****m | 7 |
| and 78 more... | ||
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0