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**.

R is one of the most popular programming languages among data analysts and data scientists. R has a wide community that will always help you with any problem. Also, R has tons of different packages designed to solve various problems. The language can be easily applied to statistics and data analytics problems. In the first part, you will be introduced to the very basics of R and will deal with single 1-D values of different types.

In the initial section, you’ll dive into the foundational elements of R, such as generating output and performing elementary operations. This section will conclude with an exploration of the theory behind variables.

You’ll become familiar with the vector class in R, which also handles individual values. Here, you’ll delve into the primary data types for singular values and learn how to manage multiple values of the same type simultaneously.

Factors, also known as categorical variables, are prevalent in the real world. Examples include blood types, currencies, nationalities, and brands. Unlike numerical variables, factors have a limited set of possible values.

Using the print() Function

Solution

Awesome!

Using the print() Function

Solution

Awesome!