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Introduction to Data Analysis and Visualization with R

Data Types in R

Explore the various data types in R such as strings, integers, doubles, logical, and complex numbers. Understand how to identify and convert these types using functions like class() and is.numeric(). This lesson helps you handle data efficiently, optimize storage, and prepare data effectively for analysis and visualization tasks.

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Data types in R

Data elements have specific characteristics depending on their format. Although two pieces of data may look the same, the way they act can be marginally different. Therefore, we need to understand the features of data types and learn how to use these features when needed.

Utilizing the appropriate data types in a project can assist us in conserving both time and energy. Knowing how to work with data types and how to modify them as needed are vital skills for a competent analyst—this will set you apart from those with less experience.

We can use the class() method to see the type of variable that stores the data.

R
# Check the data type of the variable
myNumber <- 4
print(class(myNumber))
# Check the type of the data itself
class(4)

Strings (characters)

Strings in R can be composed of any kind of character, as long as they are surrounded by '' or "". For example, even a numeric character like 3 converts to a string if wrapped with quotation marks.

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