https://github.com/njtierney/rmd4sci

Rmarkdown for Scientists
https://github.com/njtierney/rmd4sci

book bookdown data-science r rmarkdown rstats science

Last synced: 14 days ago
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Rmarkdown for Scientists

• Host: GitHub
• URL: https://github.com/njtierney/rmd4sci
• Owner: njtierney
• License: other
• Created: 2018-11-02T05:56:00.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2022-10-12T02:28:31.000Z (about 2 years ago)
• Last Synced: 2024-10-12T21:19:46.966Z (29 days ago)
• Topics: book, bookdown, data-science, r, rmarkdown, rstats, science
• Language: RMarkdown
• Homepage: https://rmd4sci.njtierney.com/
• Size: 3.25 MB
• Stars: 127
• Watchers: 8
• Forks: 40
• Open Issues: 17
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: citations-and-styles.Rmd

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README

        
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

# Rmarkdown for Scientists 

This is a book on rmarkdown, aimed for scientists. It was initially developed as a 3 hour workshop, but is now developed into a resource that will grow and change over time as a **living book**.

This book aims to teach the following:

- Getting started with your own R Markdown document

- Improve workflow:

  - With rstudio projects

  - Using keyboard shortcuts

- Export your R Markdown document to PDF, HTML, and Microsoft Word

- Better manage figures and tables

    - Reference figures and tables in text so that they dynamically update

    - Create captions for figures and tables

    - Change the size and type of figures

    - Save the figures to disk when creating an rmarkdown document

- Work with equations

    - inline and display

    - caption equations

    - reference equations

- Manage bibliographies

  - Cite articles in text

  - generate bibliographies

  - Change bibliography styles

- Debug and handle common errors with rmarkdown

- Next steps in working with rmarkdown - how to extend yourself to other rmarkdown formats

# Abstract aka "why should you read this"

For a scientific report to be completely credible, it must be reproducible. The full computational environment used to derive the results, including the data and code used for statistical analysis should be available for others to reproduce.

R Markdown is a tool that allows you integrate your code, text and figures in a single file in order to make high quality, reproducible reports. A paper published with an included R Markdown file and data sets can be reproduced by anyone with a computer.

After completing this course, you will know how to:

- Create your own R Markdown document

- Create figures and tables that you can reference in text, and update with - your data

- Export your R Markdown document to PDF, HTML, and Microsoft Word

- Use keyboard shortcuts to improve workflow

- Cite research articles and generate a bibliography

We may, depending on time, also cover the following areas:

- Change the size and type of your figures

- Create captions for your figures, and reference them in text

- Cite research articles and generate a bibliography

- Debug and handle common errors

# License 


This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.