Summary  
Comments are non-executable annotations introduced with the `#` symbol that the interpreter ignores, used to explain code logic or temporarily disable lines during debugging.

General domain of usage  
Code documentation

**Comments** are notes written inside the code that are not executed.

Definition

They are used to explain the purpose of code, provide context, or temporarily deactivate lines during debugging.

## Creating Comments
To add a comment, use the `#` symbol. Everything after `#` on the same line will be ignored by R.

# A standalone comment
11 + 3  # Adding eleven and three

In this example, the console displays only the result of `11 + 3` and ignores the comments.

## Best Practices
- Use comments to clarify complex parts of the code;
- Avoid over-commenting, as it can clutter the script;
- Use comments to disable lines temporarily during debugging.

Gain a solid understanding of R, one of the most widely used languages for data analysis. Explore fundamental data types and one-dimensional values, then advance to multi-dimensional structures, including matrices, data frames, and lists. Build the skills needed to apply R effectively in statistical analysis and data-driven decision-making.

Learn the essentials of R syntax, such as arithmetic, variables, printing functions, and comments. Strengthen your understanding of computational logic through exercises.

Explore R's data types and understand their role in data handling. Build skills in working with vectors as essential structures for organizing and analyzing information.

Develop the ability to manage categorical data effectively. Discover how to structure, group, and interpret values by converting raw data into clear categories.

Understand how to represent and work with structured two-dimensional data. Build confidence in transforming, labeling, and applying operations to matrices for analytical tasks.

Master the most widely used data structure in R for tabular information. Learn to organize, transform, and extract insights from datasets to support data-driven decisions.

Learn how lists extend beyond vectors by storing elements of different types and lengths. Develop the ability to create, access, and modify lists for organizing complex data structures.

Comments

Creating Comments

Example

Best Practices

Solution

Awesome!

Comments

Creating Comments

Example

Best Practices

Solution