Mastering R Markdown: An Essential Skill for R Programmers
Today, we will pick up where we left off in the previous lesson. If you haven’t seen the previous lessons, please catch up. We’re not far, so you can jump in here if necessary.
We already have an R Markdown file established for us because we created a new project called “Project One.” Our project files are here to the right, and we have some code and our console at the bottom.
In this lesson, we will explore some R Markdown capabilities that will create pretty cool HTML files.
As always, the video tutorial is at the bottom of this blog.
Creating Links in R Markdown
Previously, we created an HTML file with links, headers, plots, and tables. However, you might want to embed links within your R Markdown using actual HTML or the Markdown language, which is a little cleaner and preferred in this environment.
For example, to create a link using HTML, you can use the following code:
To create the same link using Markdown, use the following syntax:
Text Formatting in R Markdown
R Markdown also allows you to format text using simple symbols. For example, to make text bold or italic, you can use asterisks (*):
- To make the text italic, surround it with single asterisks:
- To make text bold, surround it with double asterisks:
Random Facts About R to Impress Your Friends
Here are some interesting facts about R programming that you might not know:
- R was created by Ross Ihaka and Robert Gentleman in 1993 at the University of Auckland, New Zealand.
- The name “R” is derived from the first names of its creators and is also a play on the name of another popular programming language, S.
- R’s strong focus on statistical computing and graphics makes it a popular choice for data analysis and visualization.
- R is open source, meaning anyone can contribute and use it for free.
- R has a large and active community of users and developers, which means you can find a wealth of resources and support online.
Recommended R Programming Books
To further improve your R programming skills, check out these highly recommended books:
- Machine Learning with R
- Extending Power BI with Python and R: Ingest, transform, enrich, and visualize data using the power of analytical languages
- The Book of R – A First Course in Programming and Statistics
I hope this blog post has helped you better understand R Markdown and its capabilities. If you found this post helpful, please consider sharing it on social media to help others discover these resources.
And don’t forget to subscribe to my YouTube channel to stay updated with the latest R programming tutorials and tips!