📦 R Variables – How to Declare, Assign, and Use Variables in R

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🧲 Introduction – What Are Variables in R?

In R, variables are used to store data—such as numbers, text, or logical values—that can be reused throughout your program. Unlike many other languages, R is dynamically typed, meaning you don’t have to declare a variable’s type before assigning a value.

Whether you’re storing a dataset, calculating a result, or labeling a string, variables are at the heart of R programming.

🎯 In this guide, you’ll learn:

• How to create and assign variables in R
• Different assignment operators (<-, =, ->)
• Naming conventions and rules
• How R handles data types in variables

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✍️ How to Create a Variable in R

You can create variables using either <-, =, or ->.

✅ Examples:

x <- 10        # Preferred assignment operator
y = 20         # Alternative, valid syntax
30 -> z        # Rightward assignment

You can now use these variables in expressions:

sum <- x + y + z
print(sum)

🧾 Output:

[1] 60

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📛 R Variable Naming Rules

Variable names (also called identifiers) must follow certain rules:

Rule	Example
Must start with a letter or . (not followed by a number)	total, .value
Can contain letters, numbers, dots (.), and underscores (_)	data_2025, temp.value
Case-sensitive	Score ≠ score
Cannot be a reserved keyword	❌ if, TRUE, function, else

❌ Invalid Examples:

1value <- 10   # Cannot start with a number
TRUE <- 5      # Cannot override reserved constants
_myvar <- 50   # Underscore at start is not allowed

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🔄 Assignment Operators in R

R provides three assignment operators:

Operator	Usage	Direction
<-	x <- 5	Assigns right value to left (most common)
=	x = 5	Same as <- in most cases (used in function calls)
->	5 -> x	Assigns left value to right

⚠️ Recommendation:

Use <- as the standard in scripts and functions, as it’s more idiomatic in R programming.

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🔤 Variable Types (Implicit Typing)

R automatically assigns the correct data type based on the value.

name <- "Alice"       # character
score <- 85           # numeric
is_passed <- TRUE     # logical

To check the type of a variable:

class(name)       # Output: "character"
typeof(score)     # Output: "double"
is.logical(is_passed)  # Output: TRUE

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📂 Remove or List Variables

To delete a variable:

rm(score)      # Removes 'score'

To view all active variables in your workspace:

ls()           # Lists variable names

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📌 Summary – Recap & Next Steps

Variables are the building blocks of R programming. Knowing how to define, use, and manage them allows you to write clean, efficient, and scalable R code.

🔍 Key Takeaways:

• Use <- for assigning values (e.g., x <- 10)
• R is case-sensitive (var ≠ Var)
• Variable names must not start with numbers or use reserved keywords
• Use rm() to remove variables and ls() to view them
• R automatically assigns data types to variables

⚙️ Real-World Relevance:
Variables allow data scientists to store values, manage datasets, create transformations, and build machine learning models efficiently in real-world R workflows.

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❓ FAQs – R Variables

❓ What is the best assignment operator in R?
✅ <- is preferred and most widely used in R for clarity and consistency.

❓ Are R variables case-sensitive?
✅ Yes. age, Age, and AGE are treated as three separate variables.

❓ How can I check the type of a variable in R?
✅ Use class() or typeof() functions:

class(x)      # "numeric", "character", etc.

❓ Can I reassign a variable with a different data type?
✅ Yes. R allows reassignment:

x <- 10
x <- "Now I am text"

❓ How do I remove all variables at once?
✅ Use:

rm(list = ls())

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