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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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The difference between <- and = assignment in R

May 5, 2020 April 5, 2021
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When I started coding in R, a couple of years ago, I was stunned by the assignment operator. In most — if not all — coding languages I know, assignment is done through the equal sign ‘=’, while in R, I was taught to do it through the backarrow ‘<-‘. It didn’t take long until I realized the equal symbol also works. So… what is correct?

Let’s say we would like to assign the value 3 to the variable x. There’s multiple ways to do that.

The first five lines of code do exactly the same. The last one is slightly different. The assign function is the OG here: it assigns a value to a variable, and it even comes with more parameters that allow you to control which environment to save them in. By default, the variable gets stored in the environment it is being run in.

The arrows are respectively the leftwards assignment and the rightwards assignment. They simply are shortcuts for assign() . The double arrow in the last line is somewhat special. First, it checks if the variable already exists in the local environment, and if it doesn’t, it will store the variable in the global environment (.GlobalEnv). If you are unfamiliar with this, try reading up on scope in programming.

So why the arrow? Apparently, this is legacy from APL , a really old programming language. R (created in the early nineties) is actually a modern implementation of S (created in the mid-70’s), and S is heavily influenced by APL. APL was created on an Execuport, a now antique machine with a keyboard that had an “arrow” symbol, and it could be generated with one keystroke.

Historically, the = symbol was used to pass arguments to an expression. For example

In 2001, to bring assignment in R more in line with other programming languages, assignment using the = symbol was implemented. There are restrictions, however. According to the documentation , it can only be used at the top-level environment, or when isolated from the surrounding logical structure (e.g. in a for loop).

But this is not necessarily true. By putting brackets around an assignment, in places where intuitively it shouldn’t work, one can get around these restrictions. There’s probably not many use cases where you would want it, but it does work. In the following example, I calculate the mean of 3, 20 and 30 and at the same time assign 3 to x.

My personal advice is to use <- for assignment and = for passing arguments. When you mix things up, weird things can happen. This example from R Inferno produces two different results.

By the way, if two keystrokes really bug you. There’s a shortcut in RStudio to generate the arrow: Alt + -. Well yes, shortcut? You still need to press two keys ;-).

By the way, if you’re having trouble understanding some of the code and concepts, I can highly recommend “An Introduction to Statistical Learning: with Applications in R”, which is the must-have data science bible . If you simply need an introduction into R, and less into the Data Science part, I can absolutely recommend this book by Richard Cotton . Hope it helps!

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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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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.

R Data Structures

R statistics, r operators.

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:

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:

R Logical Operators

Logical operators are used to combine conditional statements:

R Miscellaneous Operators

Miscellaneous operators are used to manipulate data:

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

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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.

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.

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.

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 .

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.

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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R data types and variables, r operators, r data structures, r control structures, r functions, r input and output, r data manipulation, r data cleaning, r data visualization, r statistical analysis, r programming concepts, advanced r topics, r for data science, r reporting and presentation, r assignment operators.

Assignment operators in R are essential tools for storing values in variables. They allow programmers to create, modify, and manipulate data efficiently within their R scripts.

Basic Assignment Operator

The most common assignment operator in R is the arrow ( <- ). It assigns values to variables from right to left.

R also supports the equal sign ( = ) for assignment, but it's less commonly used and may cause confusion in certain contexts.

Right-to-Left Assignment

While less common, R allows right-to-left assignment using the -> operator.

Compound Assignment Operators

R provides compound assignment operators that combine arithmetic operations with assignment. These operators perform calculations and assign the result in a single step.

+= : Add and assign
-= : Subtract and assign
*= : Multiply and assign
/= : Divide and assign

Global Assignment

The <<- operator performs a global assignment, allowing you to assign values to variables in the global environment from within functions.

Best Practices

Use descriptive variable names for clarity
Prefer <- over = for consistency
Use global assignment ( <<- ) sparingly to avoid unintended side effects
Consider using R Variables to store and manage your data effectively

Understanding assignment operators is crucial for efficient R Data Type Conversion and manipulation. They form the foundation for more advanced operations in R programming.

Related Concepts

To deepen your understanding of R programming, explore these related topics:

R Arithmetic Operators
R Comparison Operators
R Logical Operators

By mastering assignment operators and related concepts, you'll be well-equipped to write efficient and effective R code for various data analysis and manipulation tasks.

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.

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1. Assignment operator The property of the assignment
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Assignment Operators in R (3 Examples)
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r
@ClarkThomborson The semantics are fundamentally different because in R assignment is a regular operation which is performed via a function call to an assignment function. However, this is not the case for = in an argument list. In an argument list, = is an arbitrary separator token which is no longer present after parsing. After parsing f(x = 1), R sees (essentially) call("f", 1).
Assignment Operators in R (3 Examples)
Then, we could use the following R code: mean (x = 1: 5) # Does NOT save values in x # 3. ... How to use different assignment operators in R - 3 R programming examples - R programming language tutorial - Actionable R programming syntax in RStudio . Subscribe to the Statistics Globe Newsletter.
R Operators (With Examples)
R Assignment Operators. These operators are used to assign values to variables. Operator Description; Leftwards assignment->, ->> Rightwards assignment: The operators <-and = can be used, almost interchangeably, to assign to variables in the same environment.
The difference between <- and = assignment in R
When I started coding in R, a couple of years ago, I was stunned by the assignment operator. In most — if not all — coding languages I know, assignment is done through the equal sign '=', while in R, I was taught to do it through the backarrow '<-'. ... The first five lines of code do exactly the same. The last one is slightly ...
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
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
With our online code editor, you can edit code and view the result in your browser. Videos. Learn the basics of HTML in a fun and engaging video tutorial. ... 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 ...
R Operators [Arithmetic, Logical, ... With Examples]
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 = ... 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. x <- 3 x = 26 rnorm(n ...
R Assignment Operators
Basic Assignment Operator. The most common assignment operator in R is the arrow (<-). It assigns values to variables from right to left. x <- 5 y <- "Hello" R also supports the equal sign (=) for assignment, but it's less commonly used and may cause confusion in certain contexts. Right-to-Left Assignment. While less common, R allows right-to ...
Assignment Operators in R
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. # Correct usage of = for specifying function arguments plot(x = 1:10, y = rnorm(10), type ...

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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Assignment Operators in R – Which One to Use and Where

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Equal or “arrow” as an Assignment Operator?

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R Data Structures

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R operators

Arithmetic operators

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Relational / comparison operators in R

Assignment operators in R

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Infix operator

Pipe operator in R

Introduction to R

Basic Assignment Operator

Right-to-Left Assignment

Compound Assignment Operators

Global Assignment

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Assignment Operators in R

Using the <- Operator

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Quiz: Assignment Operator Best Practices

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