Summary  
Demonstrates how to use the print() function to output expressions and control the number of significant figures when printing numerical results.

General domain of usage  
Data analysis

After running the code in the previous chapter, you may have noticed `[1]` preceding the results. This is R's way of indicating that the line starts with the **first element** in your output. As you progress through the course, you'll encounter outputs with **multiple elements**.

Let's say we want to carry out a division operation:

As we already know, in R, it's **unnecessary** to use a specific function to display output values. However, if your goal is to **round** a number to a desired number of significant figures, you can use the `print()` function, which you may also recognize from other programming languages.

Here's how you use the function:

```r
print(expression, digits = n)
```

For instance, we can round the division result from our previous example to **three significant figures**:

As demonstrated, the output of the expression has been rounded to **three significant figures**.

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.

Using the print() Function

Solución

Awesome!

Using the print() Function

Solución

Awesome!