Understanding **data types** is fundamental in R programming as they dictate how data is stored, interpreted, and manipulated, so let's explore the various data types in R and their characteristics.

Each data type serves specific purposes and ensures that the data is handled appropriately according to its nature.

Here are the most common data types in R:

To determine the **data type** of a given variable, you would use the `typeof()` function, providing the respective **variable name** as its argument. For example:

Take the initiative to practice this function on your own!

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.

Data Types

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Data Types

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