Difference Between R MarkDown and R NoteBook

In this article, we will learn about two very commonly used R interfaces that is R MarkDown and R Notebook then we will also compare the two to analyze the difference between the two.

What is R MarkDown?

For building dynamic texts in R Programming Language that are simple to share and recreate using the R Markdown file format. It enables you to create and run R code within a single document and then display the outcome in a variety of forms, such as HTML, PDF, and MS Word.

A set of tools collectively known as R Markdown is facilitated by RStudio that enables the generation of “meaningful” statistical analyses, promoting transparency, self-explanation, and reproducibility in the analysis process. Literate statistical computing facilitates reproducibility by explicitly describing the analysis steps in both written text and code, enabling easy verification and reproduction of analyses from the literate code, and serving as a template for future analyses. With R Markdown, statistical documents can be produced that integrate prose, code, figures, and formatted mathematics, making it efficient and readable to share and explain analyses with collaborators, supervisors, and future selves. R Markdown documents are written in a simple plain text markup language called Markdown, originally designed for creating web pages and blogs but now adopted for various purposes.

What is R NoteBook?

R Notebook is an interactive document format that integrates narrative text, data visualizations, and other multimedia components with implemented code written in the R programming language. It enables users to produce and distribute documents with data analysis, visualization, and interpretations of the source code and data.

Additionally, R Notebook enable the incorporation of other media types, such as images and videos, making them an effective tool for presenting and sharing data analysis results. Overall, R Notebooks are a powerful and flexible tool that can enhance the efficiency and effectiveness of data analysis workflows.

R Notebook Vs R Markdown

1. R Markdown allows you to form dynamic documents that incorporate R code and text.  It is a lightweight markup language while R Notebook is an interactive notebook interface that allows you to compile R code, visualize output, and form documents in real-time.
2. R Markdown has complete support for LaTeX (A less-overhead procedure or writing reports that include R code and self-generated output), which shows that you can use LaTeX commands and syntax can be used to format text and create equations, tables, and figures in your document moreover R Notebook also supports LaTeX, but it is not as completely integrated as in R Markdown. You have to use the HTML output format and include LaTeX code in HTML code blocks.
3. R Markdown documents are executed in a non-interactive R environment using the knitr( a lightweight API and literate programming engine designed to provide complete control of the output ) package to process code chunks and give output while R Notebook allows for interactive code chunks, which means you can run code and view output directly in the document. This is useful for exploratory analysis and data visualization.
4. R Markdown is designed for creating documents with a wide range of output formats, including HTML, PDF, and Microsoft Word, and R Notebook is designed for interactive use and is ideal for sharing analysis and results with others in real-time.

Among the variety of options provided by RStudio R Markdown and R NoteBook is one of them which have minimal differences, by selecting either of them we come to glance at the R Markdown file with a slighter difference. While creating a new R Notebook it adds _{html_notebook} in the output option in the header.

# The initialization of the .rmd file has the following code.

——-
title: “Example of R Notebook”
output: 
 html_document:
   toc: true
   toc_depth: 3
   toc_float: true
——-

Creating an R Notebook

In this tutorial, we will be creating an R Markdown document known as an “R Notebook”. According to the R Notebook Documentation, an R Notebook is a type of R Markdown document that contains code chunks that can be run without any dependence. Any output generated by the code is displayed immediately below the input.

select File > New File > R Notebook from the files in RStudio.

Creating an R Notebook

Inserting Chunks in R Markdown

In R Markdown, a chunk is a code block that can be executed and displayed within a document. Chunks are enclosed within two sets of three backticks and can be labeled with optional chunk options that modify the chunk’s behavior or appearance. When an R Markdown document is rendered, chunks are executed in the order in which they appear in the document, and their output is displayed inline with the text or in a separate output section.

• This is an R Markdown Notebook. After executing this code in the notebook, the following result would be displayed.
• When you’ll click on the run button to execute this chunk by pressing Ctrl+Shift+Enter or clicking the cursor the mentioned output will be displayed.
• Click on the insert button on the toolbar or press Ctrl+Alt+I to add a new chunk.
• After saving the notebook an HTML file with its code and output will be saved.
• Press Ctrl+Shift+K or click on the preview button to view the HTML file.

In R Markdown, code blocks are defined by enclosing them within two sets of three backward ticks (“`). The contents of a code block are treated as R commands and are executed by the R interpreter. An example of a code block can be found in the default notebook template, which is typically the first one in the document.

To execute a specific code block in R Markdown, you can click the small green “Run” button located in the upper right-hand corner of the block. This button enables you to run the code within the block without executing the entire document.

When you click the “Run” button for a code block in R Markdown, the commands within that block are compiled, and any resulting output is displayed beneath the block. For instance, you can try running the first code block in the default template to see how it works. Once you compile the chunk, you should see a plot displayed within your R Notebook, as illustrated below:

R

plot(cars)

Output:

Difference between R MarkDown and R NoteBooka 

R Notebook	R Markdown
R NoteBook is denoted by .rmd with a special YAML header that signifies it as a notebook.	R MarkDown is denoted by .Rmd file extension.
They are knitted to generate reports, presentations, and other documents	They are knitted to create HTML, PDF, and Word documents, but the output will not include interactive code cells.
R Notebooks allow users to execute cells in any order.	R Markdown files require cells to be executed in order from top to bottom.
It has a more notebook-like layout with cells for code, text, and output.	It documents more linear and follows a more traditional document structure.
R Notebooks allow for interactive code execution.	R Markdown only supports static code execution.
It allows for dynamic and interactive data visualization.	R Markdown linearly documents only allow for static visualization.
It provides more flexibility in terms of output options and allows for the customization of output formats like HTML, PDF, and Word.	It doesn’t provide more flexibility in terms of output options and allows for the customization of output formats
R Markdown is primarily used for documentation purposes	R Notebooks are used for interactive data analysis and exploration.
They can automatically install required packages for code execution.	They require packages to be installed manually or specified in the YAML header.
R Notebooks maintain the state of the R environment across cells.	R Markdown documents do not.
R Notebooks are better suited for smaller analyses or exploratory work.	R Markdown is better suited for larger-scale projects with more complex requirements.

Features of R Notebook and R Markdown

1. Interactive widgets are offered by both R Notebook and R Markdown, allowing users to manipulate and interact with data directly within the document using features such as sliders, drop-down lists, and buttons. This capability can improve the user experience and promote more adaptable data exploration and analysis.
2. R Notebook and R Markdown facilitate the inline execution of R code, which allows users to insert code into markdown or text elements and run it directly within the document. This feature enables the creation of self-contained, dynamic documents that can be easily edited and updated.
3. R Notebook and R Markdown utilize code caching to enhance performance and minimize execution time. This technique involves storing previously executed code in memory and reusing it as needed, which can be especially advantageous for lengthy or computationally intensive analyses.
4. R Notebook and R Markdown are constructed using the Knitr package, which offers robust capabilities for producing top-notch reports and documents from R code. Knitr empowers users to generate personalized output formats, integrate external data sources, and seamlessly incorporate them with various tools and platforms.
5. R Notebook and R Markdown provide abundant options for customization and theming, enabling users to adjust the design and functionality of their documents according to their preferences. This includes the capacity to customize fonts, colors, and styles, as well as to integrate logos, headers, and footers.

Application of R Notebook and R Markdown

1. R Notebook and R Markdown are useful tools for various data analysis tasks, such as data cleaning, exploration, and visualization. The interactive widgets and inline code execution features allow for easy data manipulation and analysis directly within the document.
2. For reproducible research, R Notebook and R Markdown are ideal due to their literate programming approach and the ability to include text, code, and output in one document. These features make it easy to communicate research findings and share code and data with collaborators.
3. Generating high-quality reports, presentations, and manuscripts is made possible by R Notebook and R Markdown’s ability to customize and theme documents according to user needs. Users can create visually appealing and professional-looking documents using the available options.
4. R Notebook and R Markdown are also suitable for teaching data analysis, programming, and statistics. The capability of including text, code, and output into one document makes it easy for teachers to provide examples, exercises, and solutions to students.