r assignment operator difference

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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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Assignment Operators

Description.

Assign a value to a name.

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 .

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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R Operator Precedence and Associativity

R Program to Add Two Vectors

In this article, you will learn about different R operators with the help of examples.

R has many operators to carry out different mathematical and logical operations. Operators perform tasks including arithmetic, logical and bitwise operations.

• Type of operators in R

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

• Arithmetic Operators
• Relational Operators
• Logical Operators
• Assignment Operators
• 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.

Let's look at an example illustrating the use of the above operators:

• R Relational Operators

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

Let's see an example for this:

• 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 the shorter one are 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.

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 in a single length logical vector.

Zero is considered FALSE and non-zero numbers are taken as TRUE . Let's see an example for this:

• R Assignment Operators

These operators are used to assign values to variables.

The operators <- and = can be used, almost interchangeably, to assign to variables 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.

Check out these examples to learn more:

• Add Two Vectors
• Take Input From User
• R Multiplication Table

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• Introduction

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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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assignOps: Assignment Operators

Assignment operators, description.

Assign a value to a name.

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 backticks).

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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Browse r packages, we want your feedback.

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Global vs. local assignment operators in R ( <<- vs. <- )

Understanding the difference between local and global assignment operators in R can be tricky to get your head around. Here’s an example which should clear things up.

First, let’s create two variables named “global_var” and “local_var” and give them the values “global” and “local”, respectively. Notice we are using the standard assignment operator <- for both variables.

Next, let’s create a function to test out the global assignment operator ( <<- ). Inside this function, we will assign a new value to both of the variables we just created; however, we will use the <- operator for the local_var and the <<- operator for the global_var so that we can observe the difference in behavior.

This function performs how you would expect it to intuitively, right? The interesting part comes next when we print out the values of these variables again.

From this result, we can see the difference in behavior caused by the differing assignment operators. When using the <- operator inside the function, it’s scope is limited to just the function that it lives in. On the other hand, the <<- operator has the ability to edit the value of the variable outside of the function as well.

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 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.

• book review

The difference between <- and = assignment in R

• May 5, 2020 April 5, 2021

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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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:

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Why do we use arrow as an assignment operator.

Posted on September 23, 2018 by Colin Fay in R bloggers | 0 Comments

[social4i size="small" align="align-left"] --> [This article was first published on Colin Fay , 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.

A Twitter Thread turned into a blog post.

In June, I published a little thread on Twitter about the history of the <- assignment operator in R. Here is a blog post version of this thread.

Historical reasons

As you all know, R comes from S. But you might not know a lot about S (I don’t). This language used <- as an assignment operator. It’s partly because it was inspired by a language called APL, which also had this sign for assignment.

But why again? APL was designed on a specific keyboard, which had a key for <- :

At that time, it was also chosen because there was no == for testing equality: equality was tested with = , so assigning a variable needed to be done with another symbol.

From APL Reference Manual

Until 2001 , in R, = could only be used for assigning function arguments, like fun(foo = "bar") (remember that R was born in 1993). So before 2001, the <- was the standard (and only way) to assign value into a variable.

Before that, _ was also a valid assignment operator. It was removed in R 1.8 :

(So no, at that time, no snake_case_naming_convention)

Colin Gillespie published some of his code from early 2000 , where assignment was made like this 🙂

The main reason “equal assignment” was introduced is because other languages uses = as an assignment method, and because it increased compatibility with S-Plus.

Readability

Nowadays, there are seldom any cases when you can’t use one in place of the other. It’s safe to use = almost everywhere. Yet, <- is preferred and advised in R Coding style guides:

• https://google.github.io/styleguide/Rguide.xml#assignment
• http://adv-r.had.co.nz/Style.html

One reason, if not historical, to prefer the <- is that it clearly states in which side you are making the assignment (you can assign from left to right or from right to left in R):

The RHS assignment can for example be used for assigning the result of a pipe

Also, it’s easier to distinguish equality comparison and assignment in the last line of code here:

Note that <<- and ->> also exist:

And that Ross Ihaka uses = : https://www.stat.auckland.ac.nz/~ihaka/downloads/JSM-2010.pdf

Environments

There are some environment and precedence differences. For example, assignment with = is only done on a functional level, whereas <- does it on the top level when called inside as a function argument.

In the first code, you’re passing x as the parameter of the median function, whereas the second one is creating a variable x in the environment, and uses it as the first argument of median . Note that it works because x is the name of the parameter of the function, and won’t work with y :

There is also a difference in parsing when it comes to both these operators (but I guess this never happens in the real world), one failing and not the other:

It is also good practice because it clearly indicates the difference between function arguments and assignation:

And this weird behavior:

Little bit unrelated but

I love this one:

Which of course is not doable with = .

Other operators

Some users pointed out on Twitter that this could make the code a little bit harder to read if you come from another language. <- is use “only” use in F#, OCaml, R and S (as far as Wikipedia can tell). 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. You can’t use it on the top level:

But as it is still understood by the parser, you can use := as an infix without any %%, for assignment, or for anything else:

You can see that := was used as an assignment operator https://developer.r-project.org/equalAssign.html :

All the previously allowed assignment operators (

Or in R NEWS 1:

• Around 29’: https://channel9.msdn.com/Events/useR-international-R-User-conference/useR2016/Forty-years-of-S
• What are the differences between “=” and “
• Assignment Operators

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