Becoming a contributor

I am on a mission to empower the data science community by creating a comprehensive database of resources to learn and teach R.

I strongly believe that collaboration is the key to success, and I am excited to invite you to be a part of this initiative. Your valuable contributions can make a significant difference in advancing the R learning ecosystem and nurturing the next generation of data scientists.

Why Contribute?

Empower the Community: By sharing your knowledge and expertise, you empower fellow data scientists, educators, and learners to excel in R.

Showcase Your Work: Contribute your R-related resources, whether it’s tutorials, books, courses, datasets, or tools, and gain recognition within the data science community.

Make a Lasting Impact: Your contributions will remain accessible to the global data science community, serving as a valuable resource for years to come.

What am I looking for?

Below is a list of our core content areas. We welcome submissions in any of these areas. Each content area is linked to its own set of notes for contributors.

  • Books/ebooks
  • Blogs
  • Courses/Slides
  • Datasets
  • Tutorials
  • Websites

Submissions can focus on any and all topics and application areas. So far we have the following topics:

Art | | Dashboards/Shiny | | Data Science | |Datasets | | Docker | | Eye-Tracking | | From R to Python | | GIT | | Learning R | | Machine Learning | | Making Websites/Blogs | | Meta-Analyses & Systematic Reviews | | Packages (How to) | | Presentations/Slides | | Professional Development (Resumes, CVs, etc) | | Quarto | | R for Neuro | | RMarkdown | | Statistics | | Teaching R | | Visualization | | Workflows |

Target audience

  1. Educators: If you are an educator using R in your curriculum, your contributions can enrich the learning experience for your students and fellow educators alike.

  2. Data Science Learners: Whether you’re just starting your journey in data science or looking to expand your R skills, our database will provide you with the resources you need to succeed.

  3. Data Science Practitioners: If you are a professional data scientist, your expertise in R can be shared to help others in the field and foster collaboration.

  4. R Enthusiasts: Individuals passionate about R programming, statistics, and data analysis who want to contribute to the growth of the R community.

Contribution Guidelines

This is an example of an entry looking at its source code:

--------------------------------------------------------

## [Art from Code](https://art-from-code.netlify.app/)

By [Danielle Navarro](https://art-from-code.netlify.app/)

Added Sun Apr 30, 2023

**What is this?**

**Excerpt from workshop site:** This workshop provides a hands-on introduction to generative art in R. You\'ll learn artistic techniques that generative artists use regularly in their work including flow fields, iterative function systems, and more. You\'ll also learn about R packages specialised for generative art. But more than that, you\'ll learn how to reuse skills you already have as part of an artistic process: with a little work, ggplot2, dplyr, and Rcpp can become an artist\'s best friends. The assumed background is that you\'re reasonably comfortable using R and RStudio, and have experience with tidyverse.

1.  Link to site here: <https://art-from-code.netlify.app/>
2.  Link to repo here: <https://github.com/rstudio-conf-2022/art-from-code>

--------------------------------------------------------

How to contribute

1. Prerequisites:

  • GitHub Account: Ensure that you have a GitHub account. If not, you can create one at https://github.com/join.

  • Familiarity with RMarkdown: Have some basic knowledge of RMarkdown for making modifications.

2. Fork the Repository:

3. Clone the Forked Repository:

  • On your local machine, open your preferred terminal or Git client.

  • Clone the forked repository to your local machine

4. Create a New Branch:

  • Create a new branch for your modifications. Name it descriptively.

5. Modify RMarkdown Page:

  • Navigate to the folder “resources’ within the cloned repository and then navigate to the folder that fits your entry the best (e.g. Art).

  • Locate the RMarkdown (.Rmd) file you want to modify and make your changes following our contribution guidelines.

  • Add the same entry to the appropriate file type if they apple (books, blogs/slides, courses/tutorials)

6. Commit Changes:

  • Save your changes in your local repository.

  • Commit your changes

7. Push Changes to Your Fork:

  • Push your local changes to your GitHub fork

8. Create a Pull Request (PR):

  • Visit your GitHub fork and navigate to the branch you just pushed.

  • Click the “New Pull Request” button.

9. Describe Your Modification:

  • Provide a clear and concise title and description for your pull request, explaining the purpose of your modification.

  • If your modification addresses a specific issue, reference it in the description.

10. Submit the Pull Request:

  • Click the “Create Pull Request” button to submit your modification.

11. Collaborate and Review:

  • Our team will review your pull request for content and formatting. Be prepared to make any necessary adjustments.

12. Merge and Acknowledgment:

  • Once your modification is approved, it will be merged into the main repository.

  • You will be acknowledged as a contributor in our project.