Extra Resources
Last updated: 2025-02-04
Checks: 2 0
Knit directory: analysis-user-group/
This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 525ffe6. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for
the analysis have been committed to Git prior to generating the results
(you can use wflow_publish or
wflow_git_commit). workflowr only checks the R Markdown
file, but you know if there are other scripts or data files that it
depends on. Below is the status of the Git repository when the results
were generated:
Ignored files:
Ignored: .DS_Store
Ignored: analysis/.DS_Store
Unstaged changes:
Modified: workflow.R
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were
made to the R Markdown (analysis/0_resources.Rmd) and HTML
(docs/0_resources.html) files. If you’ve configured a
remote Git repository (see ?wflow_git_remote), click on the
hyperlinks in the table below to view the files as they were in that
past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | f654b8d | DrThomasOneil | 2025-02-04 | Build site. |
| Rmd | e6ea78d | DrThomasOneil | 2025-02-04 | wflow_publish(c("analysis/*.Rmd")) |
| html | 4968925 | DrThomasOneil | 2025-01-30 | Build site. |
| Rmd | afccf59 | DrThomasOneil | 2025-01-30 | wflow_publish(c("analysis/*.Rmd")) |
| html | 299ff3d | DrThomasOneil | 2025-01-28 | Build site. |
| Rmd | 272b312 | DrThomasOneil | 2025-01-28 | wflow_publish(c("analysis/*")) |
| html | 023005d | DrThomasOneil | 2025-01-07 | Build site. |
| html | c893d70 | DrThomasOneil | 2025-01-06 | Build site. |
| Rmd | 8eec2ce | DrThomasOneil | 2025-01-06 | Initial Deployment |
| html | 660b0f8 | DrThomasOneil | 2025-01-06 | Build site. |
| html | 2e79a1d | DrThomasOneil | 2025-01-06 | Build site. |
| Rmd | 451a21f | DrThomasOneil | 2025-01-06 | Initial Deployment |
Stretchly
Stretchly is an open-source app designed to encourage healthy work habits by prompting regular short (30-second) and long (20-minute) breaks. I’ve found it invaluable for maintaining focus and preventing burnout. It’s highly customizable, allowing you to tailor prompts to your needs.
roadmap.sh
roadmap.sh provides structured learning pathways for various tech-related skills, from Data Science to DevOps. The Data Science and AI roadmap outlines essential topics such as mathematics, statistics, and coding, along with curated free and paid learning resources. These roadmaps are community-driven and frequently updated, making them a great guide for self-paced learning.
LinkedIn Learning
LinkedIn Learning offers a vast library of online courses covering data analysis, programming (including R and Python), statistics, research skills, and professional development. There is a short R for Data Science course that is quite nice.
You should have access to LinkedIn Learning through your University email. Otherwise, WIMR staff can apply for a license through WIMR.
