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Assignment Operators in R (3 Examples) | Comparing = vs. ＜- vs. ＜＜-

On this page you’ll learn how to apply the different assignment operators in the R programming language .

The content of the article is structured as follows:

Let’s dive right into the exemplifying R syntax!

Example 1: Why You Should Use ＜- Instead of = in R

Generally speaking, there is a preference in the R programming community to use an arrow (i.e. ＜-) instead of an equal sign (i.e. =) for assignment.

In my opinion, it makes a lot of sense to stick to this convention to produce scripts that are easy to read for other R programmers.

However, you should also take care about the spacing when assigning in R. False spacing can even lead to error messages .

For instance, the following R code checks whether x is smaller than minus five due to the false blank between ＜ and -:

A properly working assignment could look as follows:

However, this code is hard to read, since the missing space makes it difficult to differentiate between the different symbols and numbers.

In my opinion, the best way to assign in R is to put a blank before and after the assignment arrow:

As mentioned before, the difference between ＜- and = is mainly due to programming style . However, the following R code using an equal sign would also work:

In the following example, I’ll show a situation where ＜- and = do not lead to the same result. So keep on reading!

Example 2: When ＜- is Really Different Compared to =

In this Example, I’ll illustrate some substantial differences between assignment arrows and equal signs.

Let’s assume that we want to compute the mean of a vector ranging from 1 to 5. Then, we could use the following R code:

However, if we want to have a look at the vector x that we have used within the mean function, we get an error message:

Let’s compare this to exactly the same R code but with assignment arrow instead of an equal sign:

The output of the mean function is the same. However, the assignment arrow also stored the values in a new data object x:

This example shows a meaningful difference between = and ＜-. While the equal sign doesn’t store the used values outside of a function, the assignment arrow saves them in a new data object that can be used outside the function.

Example 3: The Difference Between ＜- and ＜＜-

So far, we have only compared ＜- and =. However, there is another assignment method we have to discuss: The double assignment arrow ＜＜- (also called scoping assignment).

The following code illustrates the difference between ＜- and ＜＜- in R. This difference mainly gets visible when applying user-defined functions .

Let’s manually create a function that contains a single assignment arrow:

Now, let’s apply this function in R:

The data object x_fun1, to which we have assigned the value 5 within the function, does not exist:

Let’s do the same with a double assignment arrow:

Let’s apply the function:

And now let’s return the data object x_fun2:

As you can see based on the previous output of the RStudio console, the assignment via ＜＜- saved the data object in the global environment outside of the user-defined function.

Video & Further Resources

I have recently released a video on my YouTube channel , which explains the R syntax of this tutorial. You can find the video below:

The YouTube video will be added soon.

In addition to the video, I can recommend to have a look at the other articles on this website.

R Programming Examples

In summary: You learned on this page how to use assignment operators in the R programming language. If you have further questions, please let me know in the comments.

assignment-operators-in-r How to use different assignment operators in R – 3 R programming examples – R programming language tutorial – Actionable R programming syntax in RStudio

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Operator	Description
	Less than
>	Greater than
	Less than or equal to
>=	Greater than or equal to
==	Equal to
!=	Not equal to

Operator	Description
	Leftwards assignment
->, ->>	Rightwards assignment

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R operators

Learn all about the R programming language operators

There are several operators in R, such that arithmetic operators for math calculations, logical, relational or assignment operators or even the popular pipe operator. In this tutorial we will show you the R operators divided into operator types. In addition, we will show examples of use of every operator.

Arithmetic operators

The R arithmetic operators allows us to do math operations , like sums, divisions or multiplications, among others. The following table summarizes all base R arithmetic operators.

Arithmetic operator in R	Description
+	Plus
–	Minus
*	Multiplication
/	Division
^	Exponential
**	Exponential
%%	Modulus
%/%	Integer divide
%*%	Matrix multiplication
%o%	Outer product
%x%	Kronecker product

In the next block of code you will find examples of basic calculations with arithmetic operations with integers.

You can also use the basic operations with R vectors of the same length . Note that the result of these operations will be a vector with element-wise operation results.

Furthermore, you can use those arithmetic operators with matrix objects, besides the ones designed for this type of object (matrix multiplication types). Check our tutorial about matrix operations to learn more.

Logical / boolean operators

In addition, boolean or logical operators in R are used to specify multiple conditions between objects. These comparisons return TRUE and FALSE values.

Logical operator in R	Description
&	Elementwise logical ‘AND’
&&	Vector logical ‘AND’
\|	Elementwise logical ‘OR’
\|\|	Vector logical ‘OR’
!	Logical negation ‘NOT’
xor()	Elementwise exclusive ‘OR’ equivalent to !( x \| y)

Relational / comparison operators in R

Comparison or relational operators are designed to compare objects and the output of these comparisons are of type boolean. To clarify, the following table summarizes the R relational operators.

Relational operator in R	Description
>	Greater than
<	Lower than
>=	Greater or equal than
<=	Lower or equal than
==	Equal to
!=	Not equal to

For example, you can compare integer values with these operators as follows.

If you compare vectors the output will be other vector of the same length and each element will contain the boolean corresponding to the comparison of the corresponding elements (the first element of the first vector with the first element of the second vector and so on). Moreover, you can compare each element of a matrix against other.

Assignment operators in R

The assignment operators in R allows you to assign data to a named object in order to store the data .

Assignment operator in R	Description
	Left assignment
=	Left assignment (not recommended) and argument assignment
	Right assignment
	Left lexicographic assignment (for advanced users)
	Right lexicographic assignment (for advanced users)

Note that in almost scripting programming languages you can just use the equal (=) operator. However, in R it is recommended to use the arrow assignment ( <- ) and use the equal sign only to set arguments.

The arrow assignment can be used as left or right assignment, but the right assignment is not generally used. In addition, you can use the double arrow assignment, known as scoping assignment, but we won’t enter in more detail in this tutorial, as it is for advanced users. You can know more about this assignment operator in our post about functions in R .

In the following code block you will find some examples of these operators.

If you need to use the right assignment remember that the object you want to store needs to be at the left, or an error will arise.

There are some rules when naming variables. For instance, you can use letters, numbers, dots and underscores in the variable name, but underscores can’t be the first character of the variable name.

Reserved words

There are also reserved words you can’t use, like TRUE , FALSE , NULL , among others. You can see the full list of R reserved words typing help(Reserved) or ?Reserved .

However, if for some reason you need to name your variable with a reserved word or starting with an underscore you will need to use backticks:

Miscellaneous R operators

Miscellaneous operators in R are operators used for specific purposes , as accessing data, functions, creating sequences or specifying a formula of a model. To clarify, the next table contains all the available miscellaneous operators in R.

Miscellaneous operator in R	Description
$	Named list or dataframe column subset
:	Sequence generator
::	Accessing functions of packages It is not usually needed
:::	Accessing internal functions of packages
~	Model formulae
@	Accessing slots in S4 classes (Advanced)

In addition, in the following block of code we show several examples of these operators:

Infix operator

You can call an operator as a function . This is known as infix operators. Note that this type of operators are not generally used or needed.

Pipe operator in R

The pipe operator is an operator you can find in several libraries, like dplyr . The operator can be read as ‘AND THEN’ and its purpose is to simplify the syntax when writing R code. As an example, you could subset the cars dataset and then create a summary of the subset with the following code:

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Assignment Operators

Description.

Assign a value to a name.

	a variable name (possibly quoted).
	a value to be assigned to .

There are three different assignment operators: two of them have leftwards and rightwards forms.

The operators <- and = assign into the environment in which they are evaluated. The operator <- can be used anywhere, whereas the operator = is only allowed at the top level (e.g., in the complete expression typed at the command prompt) or as one of the subexpressions in a braced list of expressions.

The operators <<- and ->> are normally only used in functions, and cause a search to be made through parent environments for an existing definition of the variable being assigned. If such a variable is found (and its binding is not locked) then its value is redefined, otherwise assignment takes place in the global environment. Note that their semantics differ from that in the S language, but are useful in conjunction with the scoping rules of R . See ‘The R Language Definition’ manual for further details and examples.

In all the assignment operator expressions, x can be a name or an expression defining a part of an object to be replaced (e.g., z[[1]] ). A syntactic name does not need to be quoted, though it can be (preferably by backtick s).

The leftwards forms of assignment <- = <<- group right to left, the other from left to right.

value . Thus one can use a <- b <- c <- 6 .

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language . Wadsworth & Brooks/Cole.

Chambers, J. M. (1998) Programming with Data. A Guide to the S Language . Springer (for = ).

assign (and its inverse get ), for “subassignment” such as x[i] <- v , see [<- ; further, environment .

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R Operators

Operators are the symbols directing the compiler to perform various kinds of operations between the operands. Operators simulate the various mathematical, logical, and decision operations performed on a set of Complex Numbers, Integers, and Numericals as input operands.

R Operators

R supports majorly four kinds of binary operators between a set of operands. In this article, we will see various types of operators in R Programming language and their usage.

Types of the operator in R language

Arithmetic Operators

Logical operators, relational operators, assignment operators, miscellaneous operators.

Arithmetic Operators modulo using the specified operator between operands, which may be either scalar values, complex numbers, or vectors. The R operators are performed element-wise at the corresponding positions of the vectors.

Addition operator (+)

The values at the corresponding positions of both operands are added. Consider the following R operator snippet to add two vectors:

Subtraction Operator (-)

The second operand values are subtracted from the first. Consider the following R operator snippet to subtract two variables:

Multiplication Operator (*)

The multiplication of corresponding elements of vectors and Integers are multiplied with the use of the ‘*’ operator.

Division Operator (/)

The first operand is divided by the second operand with the use of the ‘/’ operator.

Power Operator (^)

The first operand is raised to the power of the second operand.

Modulo Operator (%%)

The remainder of the first operand divided by the second operand is returned.

The following R code illustrates the usage of all Arithmetic R operators.

Output

Logical Operators in R simulate element-wise decision operations, based on the specified operator between the operands, which are then evaluated to either a True or False boolean value. Any non-zero integer value is considered as a TRUE value, be it a complex or real number.

Element-wise Logical AND operator (&)

Returns True if both the operands are True.

Element-wise Logical OR operator (|)

Returns True if either of the operands is True.

NOT operator (!)

A unary operator that negates the status of the elements of the operand.

Logical AND operator (&&)

Returns True if both the first elements of the operands are True.

Logical OR operator (||)

Returns True if either of the first elements of the operands is True.

The following R code illustrates the usage of all Logical Operators in R:

The Relational Operators in R carry out comparison operations between the corresponding elements of the operands. Returns a boolean TRUE value if the first operand satisfies the relation compared to the second. A TRUE value is always considered to be greater than the FALSE.

Less than (<)

Returns TRUE if the corresponding element of the first operand is less than that of the second operand. Else returns FALSE.

Less than equal to (<=)

Returns TRUE if the corresponding element of the first operand is less than or equal to that of the second operand. Else returns FALSE.

Greater than (>)

Returns TRUE if the corresponding element of the first operand is greater than that of the second operand. Else returns FALSE.

Greater than equal to (>=)

Returns TRUE if the corresponding element of the first operand is greater or equal to that of the second operand. Else returns FALSE.

Not equal to (!=)

Returns TRUE if the corresponding element of the first operand is not equal to the second operand. Else returns FALSE.

The following R code illustrates the usage of all Relational Operators in R:

Assignment Operators in R are used to assigning values to various data objects in R. The objects may be integers, vectors, or functions. These values are then stored by the assigned variable names. There are two kinds of assignment operators: Left and Right

Left Assignment (<- or <<- or =)

Assigns a value to a vector.

Right Assignment (-> or ->>)

Assigns value to a vector.

Miscellaneous Operator are the mixed operators in R that simulate the printing of sequences and assignment of vectors, either left or right-handed.

%in% Operator

Checks if an element belongs to a list and returns a boolean value TRUE if the value is present else FALSE.

%*% Operator

$A_{r*c} x B_c*r -> P_{r*r}$

The following R code illustrates the usage of all Miscellaneous Operators in R:

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Assignment & evaluation.

The first operator you’ll run into is the assignment operator. The assignment operator is used to assign a value. For instance we can assign the value 3 to the variable x using the <- assignment operator. We can then evaluate the variable by simply typing x at the command line which will return the value of x . Note that prior to the value returned you’ll see ## [1] in the command line. This simply implies that the output returned is the first output. Note that you can type any comments in your code by preceding the comment with the hashtag ( # ) symbol. Any values, symbols, and texts following # will not be evaluated.

Interestingly, R actually allows for five assignment operators:

The original assignment operator in R was <- and has continued to be the preferred among R users. The = assignment operator was added in 2001 primarily because it is the accepted assignment operator in many other languages and beginners to R coming from other languages were so prone to use it. However, R uses = to associate function arguments with values (i.e. f(x = 3) explicitly means to call function f and set the argument x to 3. Consequently, most R programmers prefer to keep = reserved for argument association and use <- for assignment.

The operators <<- is normally only used in functions which we will not get into the details. And the rightward assignment operators perform the same as their leftward counterparts, they just assign the value in an opposite direction.

Overwhelmed yet? Don’t be. This is just meant to show you that there are options and you will likely come across them sooner or later. My suggestion is to stick with the tried and true <- operator. This is the most conventional assignment operator used and is what you will find in all the base R source code…which means it should be good enough for you.

Lastly, note that R is a case sensitive programming language. Meaning all variables, functions, and objects must be called by their exact spelling:

Assignment Operators in R

R provides two operators for assignment: <- and = .

Understanding their proper use is crucial for writing clear and readable R code.

Using the <- Operator

For assignments.

The <- operator is the preferred choice for assigning values to variables in R.

It clearly distinguishes assignment from argument specification in function calls.

Readability and Tradition

This usage aligns with R’s tradition and enhances code readability.

Using the = Operator

The = operator is commonly used to explicitly specify named arguments in function calls.

It helps in distinguishing argument assignment from variable assignment.

Assignment Capability

While = can also be used for assignment, this practice is less common and not recommended for clarity.

Mixing Up Operators

Potential confusion.

Using = for general assignments can lead to confusion, especially when reading or debugging code.

Mixing operators inconsistently can obscure the distinction between assignment and function argument specification.

In the example above, x = 10 might be mistaken for a function argument rather than an assignment.

Best Practices Recap

Consistency and clarity.

Use <- for variable assignments to maintain consistency and clarity.

Reserve = for specifying named arguments in function calls.

Avoiding Common Mistakes

Be mindful of the context in which you use each operator to prevent misunderstandings.

Consistently using the operators as recommended helps make your code more readable and maintainable.

Quiz: Assignment Operator Best Practices

Which of the following examples demonstrates the recommended use of assignment operators in R?

my_var = 5; mean(x = my_var)
my_var <- 5; mean(x <- my_var)
my_var <- 5; mean(x = my_var)
my_var = 5; mean(x <- my_var)
The correct answer is 3 . my_var <- 5; mean(x = my_var) correctly uses <- for variable assignment and = for specifying a named argument in a function call.

assign_ops {roperators}

R Documentation

Assignment operators

Description.

Modifies the stored value of the left-hand-side object by the right-hand-side object. Equivalent of operators such as += -= *= /= in languages like c++ or python. %+=% and %-=% can also work with strings.

	a stored value
	value to modify stored value by

Ben Wiseman, [email protected]

assignOps {base}

R Documentation

Assignment Operators

Description.

Assign a value to a name.

	a variable name (possibly quoted).
	a value to be assigned to .

There are three different assignment operators: two of them have leftwards and rightwards forms.

The operators <<- and ->> cause a search to made through the environment for an existing definition of the variable being assigned. If such a variable is found then its value is redefined, otherwise assignment takes place globally. Note that their semantics differ from that in the S language, but are useful in conjunction with the scoping rules of R . See ‘The R Language Definition’ manual for further details and examples.

In all the assignment operator expressions, x can be a name or an expression defining a part of an object to be replaced (e.g., z[[1]] ). The name does not need to be quoted, though it can be.

The leftwards forms of assignment <- = <<- group right to left, the other from left to right.

value . Thus one can use a <- b <- c <- 6 .

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language . Wadsworth & Brooks/Cole.

Chamber, J. M. (1998) Programming with Data. A Guide to the S Language . Springer (for = ).

assign , environment .

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Assignment Operators in R – Which One to Use and Where

Assignment Operators

R has five common assignment operators:

Many style guides and traditionalists prefer the left arrow operator, <- . Why use that when it’s an extra keystroke? <- always means assignment. The equal sign is overloaded a bit taking on the roles of an assignment operator, function argument binding, or depending on the context, case statement.

Equal or “arrow” as an Assignment Operator?

In R, both the equal and arrow symbols work to assign values. Therefore, the following statements have the same effect of assigning a value on the right to the variable on the left:

There is also a right arrow, -> which assigns the value on the left, to a variable on the right:

All three assign the value of forty-two to the variable x .

So what’s the difference? Are these assignment operators interchangeable? Mostly, yes. The difference comes into play, however, when working with functions.

The equal sign can also work as an operator for function parameters.

x <- 42 y <- 18 function(value = x-y)

History of the <- Operator

The S language also didn’t have == for equality testing, so that was left to the single equal sign. Therefore, variable assignment needed to be accomplished with a different symbol, and the arrow was chosen.

There are some differences of opinion as to which assignment operator to use when it comes to = vs <-. Some believe that = is more clear. The <- operator maintains backward compatibility with S. Google’s R Style Guide recommends using the <- assignment operator, which seems to be a pretty decent reason as well. When all is said and done, though, it is like many things in programming, it depends on what your team does.

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Go Booleans (Relational and Logical Operators)

R Booleans (Comparison and Logical Operators)

Go Operators

R Operator Precedence and Associativity

R Infix Operator

R Operators

R has many operators to carry out different mathematical and logical operations.

Operators in R can mainly be classified into the following categories.

Type of operators in R

R Arithmetic Operators

These operators are used to carry out mathematical operations like addition and multiplication. Here is a list of arithmetic operators available in R.

Arithmetic Operators in R
Operator	Description
+	Addition
-	Subtraction
*	Multiplication
/	Division
^	Exponent
%%	Modulus (Remainder from division)
%/%	Integer Division

An example run

R Relational Operators

Relational operators are used to compare between values. Here is a list of relational operators available in R.

Relational Operators in R
Operator	Description
<	Less than
>	Greater than
<=	Less than or equal to
>=	Greater than or equal to
==	Equal to
!=	Not equal to

Operation on Vectors

The above mentioned operators work on vectors . The variables used above were in fact single element vectors.

We can use the function c() (as in concatenate) to make vectors in R.

All operations are carried out in element-wise fashion. Here is an example.

When there is a mismatch in length (number of elements) of operand vectors, the elements in shorter one is recycled in a cyclic manner to match the length of the longer one.

R will issue a warning if the length of the longer vector is not an integral multiple of the shorter vector.

R Logical Operators

Logical operators are used to carry out Boolean operations like AND , OR etc.

Logical Operators in R
Operator	Description
!	Logical NOT
&	Element-wise logical AND
&&	Logical AND
\|	Element-wise logical OR
\|\|	Logical OR

Operators & and | perform element-wise operation producing result having length of the longer operand.

But && and || examines only the first element of the operands resulting into a single length logical vector.

Zero is considered FALSE and non-zero numbers are taken as TRUE . An example run.

R Assignment Operators

These operators are used to assign values to variables.

Assignment Operators in R
Operator	Description
<-, <<-, =	Leftwards assignment
->, ->>	Rightwards assignment

The operators <- and = can be used, almost interchangeably, to assign to variable in the same environment.

The <<- operator is used for assigning to variables in the parent environments (more like global assignments). The rightward assignments, although available are rarely used.

Sorry about that.

Arithmetic operators

R supports the following arithmetic operators:

Addition, + , which returns the sum of two numbers.
Subtraction, - , which returns the difference between two numbers.
Multiplication, * , which returns the product of two numbers.
Division, / , which returns the quotient of two numbers.
Exponents, ^ , which returns the value of one number raised to the power of another.
Modulus, %% , which returns the remainder of one number divided by another.
Integer Division, %/% , which returns the integer quotient of two numbers.

Assignment operators

R uses the following assignment operators:

<- assigns a value to a variable from right to left.
-> assigns a value to a variable left to right.
<<- is a global version of <- .
->> is a global version of -> .
= works the same way as <- , but its use is discouraged.

Comparison operators

R has the following comparison operators:

Equal, == , which returns TRUE if two values are equal.
Not equal, != , which returns TRUE if two values are not equal.
Less than, < , which returns TRUE if left value is less than right value.
Less than or equal to, <= , which returns TRUE if left value is less than or equal to right value.
Greater than, > , which returns TRUE if left value is greater than right value.
Greater than or equal to, >= , which returns TRUE if left value is greater than or equal to right value.

Logical operators

R has the following logical operators:

Element-wise AND, & , for comparing each element and returning TRUE if both elements are TRUE .
Logical AND, && , which returns TRUE if both values are TRUE , only evaluates as many elements as necessary.
Element-wise OR, | , for comparing each element and returning TRUE if either element is TRUE .
Logical OR, || , which returns TRUE if either value is TRUE , only evaluates as many elements as necessary.
Logical NOT, ! , which returns TRUE if the associated statement is FALSE .

Note: The long form of AND and OR ( && and || ) are preferred for if statements as the short form can produce a vector value.

Miscellaneous operators

R uses the following miscellaneous operators:

The : operator creates a sequence of numbers from the left argument to the right one.
The %in% operator returns TRUE if the left argument is in the vector to the right.
The %*% operator performs matrix multiplication on two matrices.

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Operators are used to perform operations on variables and values.

In the example below, we use the + operator to add together two values:

R divides the operators in the following groups:

Arithmetic operators
Assignment operators
Comparison operators
Logical operators
Miscellaneous operators

R Arithmetic Operators

Arithmetic operators are used with numeric values to perform common mathematical operations:

Operator	Name	Example
+	Addition	x + y
-	Subtraction	x - y
*	Multiplication	x * y
/	Division	x / y
^	Exponent	x ^ y
%%	Modulus (Remainder from division)	x %% y
%/%	Integer Division	x%/%y

R Assignment Operators

Assignment operators are used to assign values to variables:

Note: <<- is a global assigner. You will learn more about this in the Global Variable chapter .

It is also possible to turn the direction of the assignment operator.

x <- 3 is equal to 3 -> x

R Comparison Operators

Comparison operators are used to compare two values:

Operator	Name	Example
==	Equal	x == y
!=	Not equal	x != y
>	Greater than	x > y
<	Less than	x < y
>=	Greater than or equal to	x >= y
<=	Less than or equal to	x <= y

R Logical Operators

Logical operators are used to combine conditional statements:

Operator	Description
&	Element-wise Logical AND operator. It returns TRUE if both elements are TRUE
&&	Logical AND operator - Returns TRUE if both statements are TRUE
\|	Elementwise- Logical OR operator. It returns TRUE if one of the statement is TRUE
\|\|	Logical OR operator. It returns TRUE if one of the statement is TRUE.
!	Logical NOT - returns FALSE if statement is TRUE

R Miscellaneous Operators

Miscellaneous operators are used to manipulate data:

Operator	Description	Example
:	Creates a series of numbers in a sequence	x <- 1:10
%in%	Find out if an element belongs to a vector	x %in% y
%*%	Matrix Multiplication	x <- Matrix1 %*% Matrix2

Note: You will learn more about Matrix multiplication and matrices in a later chapter.

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Operators in R Programming: A Complete Overview

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Operators in R Programming are fundamental components that allow you to perform various tasks in this powerful language known for statistical computing and data analysis. These Operators play a crucial role in executing mathematical computations. Having a good understanding of these components is necessary for tasks like value comparisons, logical evaluations, bit-level operations, and unique functionalities.

According to Statista , 4.23% developers worldwide use the R programming language. If you wish to understand the usage of Operators in this language, this blog is the right choice for you. These Operators are essential for unleashing the language's potential, making it an indispensable skill for any R programmer. Keep reading this blog to learn about Operators in R Programming, including arithmetic, logical, and many more types, each facilitating data manipulation and calculation.

Table of Contents

1) What are Operators in R programming?

a) Arithmetic Operators

b) Assignment Operators

c) Comparison Operators

d) Logical Operators

e) Bitwise Operators

f) Special Operators

2) Conclusion

What are Operators in R programming?

In R programming, Operators are essential elements that enable users to perform various operations on data and variables. They serve as symbols or functions that carry out specific tasks, such as mathematical computations, comparisons, logical evaluations, and bit-level operations. These Operators play a crucial role in data analysis, statistics, and other computational tasks, making them fundamental to the functionality and versatility of R programming. Some of these Operators are as follow:

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Arithmetic Operators

Arithmetic Operators perform essential mathematical computations in R, enabling calculations like addition, subtraction, multiplication, division, and modulo operations. They are crucial for numeric data manipulation and form the basis of various mathematical tasks in programming.

1) Addition: This Operator (+) is used to add two or more numeric values.

2) Subtraction: This Operator (-) is used to subtract one numeric value from another.

3) Multiplication: This Operator (*) is used to multiply two or more numeric values.

4) Division: This Operator (/) is used to divide one numeric value by another.

5) Modulo: This Operator (%) is used to find the remainder after division.

A program in R that demonstrates all arithmetic Operators

# Arithmetic Operators in R Programming

# Define two numeric variables

# Addition

addition_result

# Subtraction

subtraction_result

# Multiplication

multiplication_result

# Division

division_result

# Modulo

modulo_result

[1] "Addition Result: 13"

[1] "Subtraction Result: 7"

[1] "Multiplication Result: 30"

[1] "Division Result: 3.33333333333333"

[1] "Modulo Result: 1"

Assignment Operators

Assignment Operators are vital for assigning values to variables in R. They simplify the process of storing and updating data, making it easier to manage and manipulate data throughout a program.

1) Assignment Operator (=): The assignment Operator, denoted with the symbol (=) is used to assign a value to a variable.

2) Shortcut assignment Operators (+=, -=, =, /=): Shortcut assignment Operators are used to perform an operation and assign the result to the variable in a single step.

A program in R that demonstrates all assignment Operators

# Assignment Operators in R Programming

# Define a variable

# Use the shortcut assignment Operators

x += 3

print(paste("After using shortcut addition, x =", x))

x -= 2

print(paste("After using shortcut subtraction, x =", x))

x *= 4

print(paste("After using shortcut multiplication, x =", x))

x /= 2

print(paste("After using shortcut division, x =", x))

[1] "After using the assignment Operator, x = 15"

[1] "After using shortcut addition, x = 18"

[1] "After using shortcut subtraction, x = 16"

[1] "After using shortcut multiplication, x = 64"

[1] "After using shortcut division, x = 32"

Comparison Operators

Comparison Operators are used for comparing values or expressions, generating logical outcomes (TRUE or FALSE). They play a significant role in decision-making, conditional statements, and filtering data based on specific conditions. Here’s a list of operations:

1) Equal to (==): The equal to Operator checks if two values are equal.

2) Not Equal to (!=): The not equal to Operator checks if two values are not equal.

3) Greater than (>): The greater than Operator checks if the left operand is greater than the right operand.

4) Less than ( The less than Operator checks if the left operand is less than the right operand.

5) Greater than or Equal to (>=): The greater than or equal to Operator checks if the operand on left is greater than or equal to the operand on right.

6) Less than or Equal to ( The less than or equal to Operator checks if the operand on left is less than or equal to the operand on right.

A program in R that demonstrates all comparison Operators

# Comparison Operators in R Programming

# Define two variables

# Equal to (==)

result_equal

# Not Equal to (!=)

result_not_equal

# Greater than (>)

result_greater_than

print(paste("Greater than (a > b):", result_greater_than))

# Less than (

print(paste("Less than (a

result_greater_equal

print(paste("Greater than or Equal to (a >= b):", result_greater_equal))

# Less than or Equal to (

print(paste("Less than or Equal to (a

[1] "Equal to (a == b): FALSE"

[1] "Not Equal to (a != b): TRUE"

[1] "Greater than (a > b): TRUE"

[1] "Less than (a

[1] "Less than or Equal to (a

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Logical Operators

Logical Operators are instrumental in performing logical evaluations and combining logical values to produce new results. They are fundamental for creating complex logical expressions and controlling the flow of a program. Here’s a list of operators under this section:

1) AND (&&): The AND Operator returns TRUE if both the left and right operands are TRUE.

2) OR (||): The OR Operator returns TRUE if either the left or right operand is TRUE.

3) NOT (!): The NOT Operator is used to negate the logical value of an expression.

A program in R that demonstrates all logical Operators

# Logical Operators in R Programming

# Define two logical variables

# AND (&&)

result_and

# OR (||)

result_or

# NOT (!)

result_not_x

print(paste("NOT (!x):", result_not_x))

print(paste("NOT (!y):", result_not_y))

[1] "AND (x && y): FALSE"

[1] "OR (x || y): TRUE"

[1] "NOT (!x): FALSE"

[1] "NOT (!y): TRUE"

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Bitwise Operators

Bitwise Operators are employed for low-level bit manipulation in R. They perform operations at the bit level and are typically used in specialized programming scenarios that require direct manipulation of binary data. Given below is a list of operators under this section:

1) Bitwise AND (&): The bitwise AND Operator performs a bitwise AND operation between two integers.

2) Bitwise OR (|): The bitwise OR Operator performs a bitwise OR operation between two integers.

3) Bitwise XOR (^): The bitwise XOR Operator performs a bitwise exclusive OR operation between two integers.

4) Bitwise NOT (~): The bitwise NOT Operator performs a bitwise complement operation on an integer.

5) Left Shift ( Using the left shift Operator lets you shifts the bits of an integer to the left.

6) Right Shift (>>): Using the right shift Operator lets you shifts the bits of an integer to the right.

A program in R that demonstrates all bitwise Operators

# Install and load the 'bitops' package

install.packages("bitops")

library(bitops)

# Define two integers

# Bitwise AND (&)

result_and

# Bitwise OR (|)

result_or

# Bitwise XOR (^)

result_xor

# Bitwise NOT (~)

result_not

# Left Shift (

print(paste("Left Shift (a

result_right_shift

[1] "Bitwise AND (a & b): 1"

[1] "Bitwise OR (a | b): 7"

[1] "Bitwise XOR (a ^ b): 6"

[1] "Bitwise NOT (~a): -6"

[1] "Left Shift (a

Special Operators

Special Operators in R, like %in% and %%, serve unique functions. %in% checks for the presence of an element in a vector, while %% is utilized for matrix multiplication. They provide specialized capabilities in data manipulation and computation tasks. Given below is a list of operators in this section:

a) %in% Operator: This Operator is used to check if an element is present in a vector.

b) %*% Operator: This Operator is used for multiplication of matrix.

A program in R that demonstrates all special Operators

# Special Operators in R Programming

# Vector membership (%in%)

vector

result_in

# Matrix multiplication (%*%)

matrix1

result_multiply

print(result_multiply)

[1] "Vector Membership (element %in% vector): TRUE"

[1] "Matrix Multiplication (matrix1 %*% matrix2):"

[,1] [,2]

[1,] 19 22

[2,] 43 50

Conclusion

Operators in R Programming form the backbone of this language, empowering users to perform diverse tasks with efficiency and precision. From basic arithmetic calculations to complex data manipulations, these Operators are vital tools that elevate R's capabilities in statistical computing and data analysis, making it an invaluable language for data scientists and programmers.

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R news and tutorials contributed by hundreds of R bloggers

Difference between assignment operators in r.

Posted on January 27, 2014 by Kun Ren in R bloggers | 0 Comments

[social4i size="small" align="align-left"] --> [This article was first published on The blog of Kun Ren , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

For R beginners, the first operator they use is probably the assignment operator <- . Google's R Style Guide suggests the usage of <- rather than = even though the equal sign is also allowed in R to do exactly the same thing when we assign a value to a variable. However, you might feel inconvenient because you need to type two characters to represent one symbol, which is different from many other programming languages.

As a result, many users ask Why we should use <- as the assignment operator?

Here I provide a simple explanation to the subtle difference between <- and = in R.

First, let's look at an example.

The above code uses both <- and = symbols, but the work they do are different. <- in the first two lines are used as assignment operator while = in the third line does not serves as assignment operator but an operator that specifies a named parameter formula for lm function.

In other words, <- evaluates the the expression on its right side ( rnorm(100) ) and assign the evaluated value to the symbol (variable) on the left side ( x ) in the current environment. = evaluates the expression on its right side ( y~x ) and set the evaluated value to the parameter of the name specified on the left side ( formula ) for a certain function.

We know that <- and = are perfectly equivalent when they are used as assignment operators.

Therefore, the above code is equivalent to the following code:

Here, we only use = but for two different purposes: in the first and second lines we use = as assignment operator and in the third line we use = as a specifier of named parameter.

Now let's see what happens if we change all = symbols to <- .

If you run this code, you will find that the output are similar. But if you inspect the environment, you will observe the difference: a new variable formula is defined in the environment whose value is y~x . So what happens?

Actually, in the third line, two things happened: First, we introduce a new symbol (variable) formula to the environment and assign it a formula-typed value y~x . Then, the value of formula is provided to the first paramter of function lm rather than, accurately speaking, to the parameter named formula , although this time they mean the identical parameter of the function.

To test it, we conduct an experiment. This time we first prepare the data.

Basically, we just did similar things as before except that we store all vectors in a data frame and clear those numeric vectors from the environment. We know that lm function accepts a data frame as the data source when a formula is specified.

Standard usage:

Working alternative where two named parameters are reordered:

Working alternative with side effects that two new variable are defined:

Nonworking example:

The reason is exactly what I mentioned previously. We reassign data to data and give its value to the first argument ( formula ) of lm which only accepts a formula-typed value. We also try to assign z~x+y to a new variable formula and give it to the second argument ( data ) of lm which only accepts a data frame-typed value. Both types of the parameter we provide to lm are wrong, so we receive the message:

From the above examples and experiments, the bottom line gets clear: to reduce ambiguity, we should use either <- or = as assignment operator, and only use = as named-parameter specifier for functions.

In conclusion, for better readability of R code, I suggest that we only use <- for assignment and = for specifying named parameters.

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What is the R assignment operator := for?

By digging into R source code (file R-3.2.2/src/main/gram.y lines 2836 to 2852) I found that the R parser/tokenizer considers that := is a LEFT_ASSIGNMENT token.

But when trying to use it as an assignment operator in R.3.2.2 , I have an error (impossible to find function for := ...) but as you can see R considers it as an assignment like <- :

Is it a bug, or does the token := need to be removed from the tokenizer source code?

Is there a past story about := operator in R?

assignment-operator
colon-equals

3 := is a very handy operator inside of data.table , but not (yet?) in R as far as I know. – daroczig Commented Sep 28, 2015 at 7:56
2 Unrelated - why is half of the R error output in English? I'm assuming you have the locale set to French. – Chris Cirefice Commented Sep 28, 2015 at 11:49
Related: stackoverflow.com/questions/7033106 stackoverflow.com/questions/26269423 – Frank Commented Sep 28, 2015 at 13:29

3 Answers 3

It was a previously allowed assignment operator, see this article from John Chambers in 2001.

The development version of R now allows some assignments to be written C- or Java-style, using the = operator. This increases compatibility with S-Plus (as well as with C, Java, and many other languages). All the previously allowed assignment operators (<-, :=, _, and <<-) remain fully in effect.

It seems the := function is no longer present, but you can "re-enable it" like this:

James, FYI it seems '_' is currently not see as an assignment by the R-3.2.2 parser/tokenizer (just type it alone on the prompt and you will have an 'unexpected input' and not a 'unexpected assignment' as you will have by typing alone '<-' or ':=' or '<<-' – Romain Jacotin Commented Sep 28, 2015 at 8:47
@RomainJacotin Yes, the underscore was removed as an assignment operator in version 1.8.0, I don't find any mention in the news files regarding := though. svn.r-project.org/R/trunk/doc/NEWS.1 – James Commented Sep 28, 2015 at 8:50
4 I think they simply forgot to remove it and then Matt came along with data.table and now they can't remove it anymore. – Roland Commented Sep 28, 2015 at 9:01

To clarify, the R assignment operators are <- and = .

To get information about them type:

Instead of <- in your command line. There also exists an operator <<- affecting the variable in the parent environment.

Regarding := , this operator is the j operator in data.table package. It can be read defined as and is only usable in a data.table object. To illustrate this we modify the second column to b (define col2 with value b ) when values in the first col are equal to 1 :

For detail explanation:

Hope it clarifies.

I guess those lines in the parser's code are why := could be defined. I remember reading something like this, but forgot where. Maybe Matt or Arun could clarify. – Roland Commented Sep 28, 2015 at 8:12
Effectively the data.table packages defines a custom ':=' function that take advantages of the ':=' assignment operator that is defined in the R parser/tokenizer but it is unofficially described/written nowhere in R Language ... Next question: is it really safe and future proof for everyone (and for data.table maintainers ...) to use this ':=' token ??? Is the data.table devs ask the R core team to add this ':=' assignment token ? – Romain Jacotin Commented Sep 28, 2015 at 8:30
@RomainJacotin It is extremely unlikely that R-core would change the parser in a way that breaks the widely used data.table package. They are very careful about backwards compatibility. – Roland Commented Sep 28, 2015 at 8:33
it is usefull to define this operator as such since it acts by reference to modify a data.table object. No confusion will be made with the traditional base R operator <- , = and to a lesser extend <<- – Colonel Beauvel Commented Sep 28, 2015 at 8:35
2 @RomainJacotin CRAN is a massive test-suite for R itself - such change for R would result in hundreds of packages to fail, direct dependencies + more which depends indirectly. IMO the unused := operator in R is a feature, in fact there could be even few more operators like that. Besides, R does not provide functionality which could substitute that data.table's valuable feature so I don't know what rationale would justify the scenario mentioned by you. – jangorecki Commented Sep 28, 2015 at 13:57

(Note: This is not a direct answer to the original question. Since I don't have enough reputation to comment and I think the piece of information below is useful, I put it as an answer anyway. Please let me know if there is a better way to do so!)

Although you can't directly use := as = or <- , the := operator is very useful in programming with domain specific language (DSL) that use nonstandard evaluation (NSE), such as dplyr and data.table . Below is an example:

In the example above, replacing := within the my_mutate function with = won't work, because !! mean_name = mean(!! expr) isn't valid R code.

You can read more about NSE and programming with dplyr here . It does a great job explaining how to handle NSE when using dplyr functions to write your own function. My example above is directly copied from the website.

1 I think it's a proper answer as most will know := only from data.table and tidyverse . I would add that none of these package actually execute the code contained in their definition of := , they just use it because it has convenient and operator precedence and parse the expression that contain it when it's used in a compatible argument. – moodymudskipper Commented Nov 13, 2018 at 11:54
3 Question: do you have to import the := from somewhere? I am building a package with a function that has very similar syntax to your my_mutate() above and R CMD CHECK is giving me no visible global function definition for ‘:=’ error. Thoughts? – seth127 Commented Apr 1, 2020 at 15:28
2 Oh wait, I think I found an answer: community.rstudio.com/t/undefined-global-functions-or-variables/… short version: @importFrom rlang := – seth127 Commented Apr 1, 2020 at 15:33

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IMAGES

Assignment Operators in R (3 Examples)
R
Global vs. local assignment operators in R
Intro to R Programming Variables, Variable Naming Rules & Assignment
operators in r programming
R Operators

COMMENTS

Assignment Operators in R (3 Examples)
On this page you'll learn how to apply the different assignment operators in the R programming language. The content of the article is structured as follows: 1) Example 1: Why You Should Use ＜- Instead of = in R. 2) Example 2: When ＜- is Really Different Compared to =. 3) Example 3: The Difference Between ＜- and ＜＜-.
r
The difference in assignment operators is clearer when you use them to set an argument value in a function call. For example: median(x = 1:10) x. ## Error: object 'x' not found. In this case, x is declared within the scope of the function, so it does not exist in the user workspace. median(x <- 1:10)
R Operators (With Examples)
The above mentioned operators work on vectors. The variables used above were in fact single element vectors. We can use the function c() (as in concatenate) to make vectors in R. All operations are carried out in element-wise fashion. Here is an example. x <- c(2, 8, 3) y <- c(6, 4, 1) x + y. x > y.
R Operators [Arithmetic, Logical, ... With Examples]
R operators. There are several operators in R, such that arithmetic operators for math calculations, logical, relational or assignment operators or even the popular pipe operator. In this tutorial we will show you the R operators divided into operator types. In addition, we will show examples of use of every operator.
R: Assignment Operators
Details. There are three different assignment operators: two of them have leftwards and rightwards forms. The operators <- and = assign into the environment in which they are evaluated. The operator <- can be used anywhere, whereas the operator = is only allowed at the top level (e.g., in the complete expression typed at the command prompt) or ...
R Operators
In programming, assignment operators are essential tools for storing values in variables. In R, a statistical computing language, both "=" and "<-" are used as assignment operators, but they are not the same. Understanding their differences can enhance your coding practice and improve your code's readability and functionality. Basic Understandin
Assignment & Evaluation · UC Business Analytics R Programming Guide
The original assignment operator in R was <-and has continued to be the preferred among R users. The = assignment operator was added in 2001 primarily because it is the accepted assignment operator in many other languages and beginners to R coming from other languages were so prone to use it. However, R uses = to associate function arguments with values (i.e. f(x = 3) explicitly means to call ...
Assignment Operators in R
For Assignments. The <- operator is the preferred choice for assigning values to variables in R. It clearly distinguishes assignment from argument specification in function calls. # Correct usage of <- for assignment x <- 10 # Correct usage of <- for assignment in a list and the = # operator for specifying named arguments my_list <- list (a = 1 ...
R: Assignment operators
Assignment operators Description. Modifies the stored value of the left-hand-side object by the right-hand-side object. Equivalent of operators such as +=-= *= /= in languages like c++ or python.%+=% and %-=% can also work with strings. Usage
R: Assignment Operators
Details. There are three different assignment operators: two of them have leftwards and rightwards forms. The operators <- and = assign into the environment in which they are evaluated. The operator <- can be used anywhere, whereas the operator = is only allowed at the top level (e.g., in the complete expression typed at the command prompt) or ...
Assignment Operators in R
Whenever you start learning a new programming language, you must get accustomed to the language's syntax. One of the first operators you'd expect to come across is the assignment operator for the language. Assignment operators are used to, well, assign values to variables. The R language has a few different ways to assign values. Let's…
R Operators: Arithmetic, Relational, Logical and More
The operators <- and = can be used, almost interchangeably, to assign to variable in the same environment. The <<- operator is used for assigning to variables in the parent environments (more like global assignments). The rightward assignments, although available are rarely used. R has several operators to perform tasks including arithmetic ...
R
Operators are used in R to perform various operations on variables and values. Among the most commonly used ones are arithmetic and assignment operators. Syntax. The following R code uses an arithmetic operator for multiplication, *, to calculate the product of two numbers, along with the assignment operator, <-to store the result in the ...
R Operators
R Logical Operators. Logical operators are used to combine conditional statements: Element-wise Logical AND operator. It returns TRUE if both elements are TRUE. Elementwise- Logical OR operator. It returns TRUE if one of the statement is TRUE. Logical OR operator. It returns TRUE if one of the statement is TRUE.
How do you use "<<-" (scoping assignment) in R?
It helps to think of <<-as equivalent to assign (if you set the inherits parameter in that function to TRUE).The benefit of assign is that it allows you to specify more parameters (e.g. the environment), so I prefer to use assign over <<-in most cases.. Using <<-and assign(x, value, inherits=TRUE) means that "enclosing environments of the supplied environment are searched until the variable 'x ...
Operators in R Programming: A Complete Overview
1) Assignment Operator (=): The assignment Operator, denoted with the symbol (=) is used to assign a value to a variable. 2) Shortcut assignment Operators (+=, -=, =, /=): Shortcut assignment Operators are used to perform an operation and assign the result to the variable in a single step. A program in R that demonstrates all assignment Operators.
Assignment operators in R: '=' vs.
The Google R style guide prohibits the use of "=" for assignment. Hadley Wickham's style guide recommends "<-". If you want your code to be compatible with S-plus you should use "<-". I believe that the General R community recommend using "<-", but I can't find anything on the mailing list. However, I tend always use the ...
Why do we use arrow as an assignment operator?
Even if <-is rare in programming, I guess its meaning is quite easy to grasp, though. Note that the second most used assignment operator is := (= being the most common). It's used in {data.table} and {rlang} notably. The := operator is not defined in the current R language, but has not been removed, and is still understood by the R parser ...
Difference between assignment operators in R
For R beginners, the first operator they use is probably the assignment operator <-.Google's R Style Guide suggests the usage of <-rather than = even though the equal sign is also allowed in R to do exactly the same thing when we assign a value to a variable. However, you might feel inconvenient because you need to type two characters to represent one symbol, which is different from many other ...
Assignment operators in R: '<-' and '<<-'
7. <- assigns an object to the environment in which it is evaluated (local scope). <<- assigns an object to the next highest environment that the name is found in or the global namespace if no name is found. See the documentation here. <<- is usually only used in functions, but be careful. <<- can be much harder to debug because it is harder to ...
What is the R assignment operator := for?
The development version of R now allows some assignments to be written C- or Java-style, using the = operator. This increases compatibility with S-Plus (as well as with C, Java, and many other languages). All the previously allowed assignment operators (<-, :=, _, and <<-) remain fully in effect. It seems the := function is no longer present ...

Assignment Operators in R (3 Examples) | Comparing = vs. ＜- vs. ＜＜-

Example 1: Why You Should Use ＜- Instead of = in R

Example 2: When ＜- is Really Different Compared to =

Example 3: The Difference Between ＜- and ＜＜-

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