Logical Operators in R

In this tutorial you will learn about the *logical operators* in R with examples. Like most of the programming languages, R programming also has logical operators to perform Boolean operations.

## Logical Operators in R

Following symbols are used as logical operators in R programming language:

Operator Symbols |
Logical Operation |
Example |
---|---|---|

`!` |
Logical negation `NOT` |
`! x` |

`&` |
Element-wise logical `AND` |
`x & y` |

`&&` |
Vector logical `AND` |
`x && y` |

`|` |
Element-wise logical `OR` |
`x | y` |

`||` |
Vector logical `OR` |
`x || y` |

`xor` |
Element-wise exclusive `OR` |
`xor(x,y)` |

Suppose we have two relational expressions A and B.

Following table shows the result of various logical operations on A and B:

`A` |
`B` |
`!A` |
`A && B` |
`A || B` |
`xor(A,B)` |
---|---|---|---|---|---|

`TRUE` |
`TRUE` |
`FALSE` |
`TRUE` |
`TRUE` |
`FALSE` |

`FALSE` |
`TRUE` |
`TRUE` |
`FALSE` |
`TRUE` |
`TRUE` |

`TRUE` |
`FALSE` |
`FALSE` |
`FALSE` |
`TRUE` |
`TRUE` |

`FALSE` |
`FALSE` |
`TRUE` |
`FALSE` |
`FALSE` |
`FALSE` |

## Logical Expressions

A logical expression is an expression created using the relational operators and the logical operators. The value of the logical expression is either `TRUE`

or `FALSE`

. The example of logical expression is :

```
x <- 5
x < 4 & x >= 2
```

`[1] FALSE`

In the above R code, `x < 4`

and `x >= 2`

are the relational expressions. R evaluate the two relational expressions and in next statement, it evaluates the logical expression `x < 4 & x >= 2`

.

## Examples of Logical Operators in R

To understand the logical operators in R, lets understand logical operator in R with examples.

### Logical NOT (`!`

)

The symbol (`!`

) is the negation operator used for logical NOT.

For example,

if `A`

is `TRUE`

then `!A`

is `FALSE`

If `A`

is `FALSE`

then `!A`

is `TRUE`

```
A <- TRUE
! A
```

`[1] FALSE`

```
B <- FALSE
! B
```

`[1] TRUE`

### Logical AND (`&`

)

The symbol `&`

(single ampersand) is used for element-wise logical **AND** operator. If both the operands are `TRUE`

, result using logical and (`&`

) evaluate as `TRUE`

else result using logical and (`&`

) evaluate as `FALSE`

.

```
A <- TRUE
B <- FALSE
C <- TRUE
```

`A & B`

`[1] FALSE`

In the above R code, `A`

is `TRUE`

and `B`

is `FALSE`

. Hence the result of the `A & B`

is `FALSE`

.

`A & C`

`[1] TRUE`

In the above R code `A`

is `TRUE`

and `C`

is also `TRUE`

, the result of the `A & C`

using logical and `&`

evaluate as `TRUE`

.

### Logical OR (`|`

)

The symbol `|`

is used for element-wise logical OR. The logical expression `A | B`

is `TRUE`

if `A`

or `B`

or both are `TRUE`

(i.e., at least one of the logical value is `TRUE`

).

```
# A is TRUE, B is TRUE
A | B
```

`[1] TRUE`

```
# A is TRUE, C is FALSE
A | C
```

`[1] TRUE`

### Logical Exclusive OR (`xor()`

)

The function `xor()`

is used for element-wise exclusive logical OR. The result of `xor(A,B)`

is `TRUE`

if either `A`

or `B`

are `TRUE`

but not both.

`xor(TRUE,TRUE)`

`[1] FALSE`

`xor(TRUE,FALSE)`

`[1] TRUE`

`xor(FALSE,TRUE)`

`[1] TRUE`

`xor(FALSE,FALSE)`

`[1] FALSE`

Remember the difference between OR (`|`

) and XOR (`xor()`

). In the case of using OR (`A | B`

) operator, if at least one operand is `TRUE`

, the result is TRUE otherwise the result is `FALSE`

. In the case of using XOR (`xor(A, B)`

) operator, the result is `TRUE`

if either `A`

or `B`

is `TRUE`

but not both.

## Logical operations on Vector and scalar

Like arithmetic operators and relational operators, logical operations are also vectorized. When vector is compared with scalar using logical operator, R will recycled the scalar element to the length of vector and then perform element-wise logical operations.

### Logical NOT (`!`

)

`x <- c(12, 10, 8, 16, 6)`

`! (x < 10)`

`[1] TRUE TRUE FALSE TRUE FALSE`

In the above R code, `x`

is a vector and `10`

is a scalar.

In this example, R evaluate the relational expression `x < 10`

resulting to a logical vector `FALSE, FALSE, TRUE, FALSE, TRUE`

. Later it evaluates using logical NOT (`!`

) operation on the logical vector,results as `TRUE, TRUE, FALSE, TRUE, FALSE`

.

### Logical AND (`&`

)

`x <= 8 & x >= 5`

`[1] FALSE FALSE TRUE FALSE TRUE`

In the above examle, R evaluate the relational expression `x <= 8`

result to `FALSE, FALSE, TRUE, FALSE, TRUE`

.The relational expression `x >= 5`

result to `TRUE, TRUE, TRUE, TRUE, TRUE`

.

Later, it apply the logical AND (`&`

) on both the logical vectors, final result as `FALSE, FALSE, TRUE, FALSE, TRUE`

.

### Vector Logical AND (`&&`

)

`x <= 8 && x >= 5`

`[1] FALSE`

In the above example, R evaluate the relational expression `x <= 8`

result to `FALSE, FALSE, TRUE, FALSE, TRUE`

. The relational expression `x >= 5`

result to `TRUE, TRUE, TRUE, TRUE, TRUE`

.

Later, it apply the vector logical AND (`&&`

) on both the logical vectors,final result as `FALSE`

.

Note that the operator `&&`

evaluates from left to right and examine only the first element of both the vectors.

The shorter form `&`

performs element-wise comparison, whereas the longer form `&&`

evaluates left to right examining only the first element in each vector.

### Logical `OR`

(`|`

)

`x >= 8 | x > 6`

`[1] TRUE TRUE TRUE TRUE FALSE`

In the above R code, R evaluate the relational expression `x >= 8`

result to `TRUE, TRUE, TRUE, TRUE, FALSE`

.The relational expression `x >6`

result to `TRUE, TRUE, TRUE, TRUE, FALSE`

.

Later, it apply the logical OR (`|`

) on both the logical vectors, final result as `TRUE, TRUE, TRUE, TRUE, FALSE`

.

`x >= 8 || x <= 6`

`[1] TRUE`

In the above example, R evaluate the relational expression `x >= 8`

result to `TRUE, TRUE, TRUE, TRUE, FALSE`

. The relational expression `x <= 6`

result to `FALSE, FALSE, FALSE, FALSE, TRUE`

.

Later,it apply the vector logical OR (`||`

) on both the logical vectors, result as `TRUE`

.

Note that the operator `||`

evaluates from left to right and examine only the first element of both the vectors.

The shorter form `|`

performs element-wise comparison, whereas the longer form `||`

evaluates left to right examining only the first element in each vector.

### Logical Exclusive OR (`xor`

)

The logical exclusive OR operator `xor(a,b)`

is used when you want either `a`

or `b`

`TRUE`

but not both.

```
x <- c(12, 10, 8, 16, 6)
xor(x >= 10, x >= 6)
```

`[1] FALSE FALSE TRUE FALSE TRUE`

In the aboe R code, R evaluate the relational expression `x >= 10`

result as `TRUE, TRUE, FALSE, TRUE, FALSE`

. The relational expression `x >= 6`

result to `TRUE, TRUE, TRUE, TRUE, TRUE`

.

Later,it apply the exclusive logical OR (`xor`

) on both the logical vectors,final result as `FALSE, FALSE, TRUE, FALSE, TRUE`

.

## Logical operations on Vectors

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8, 18, 6)
```

### Logical NOT (`!`

)

`! (x <= y) `

`[1] TRUE FALSE FALSE FALSE FALSE`

R evaluate the relational expression `x <=y`

result to a logical vector `FALSE, TRUE, TRUE, TRUE, TRUE`

.

Later, it apply the negation (`!`

) to the logical vector, final result as `TRUE, FALSE, FALSE, FALSE, FALSE`

.

### Logical AND (`&`

)

`x <= y & x >= 10`

`[1] FALSE TRUE FALSE TRUE FALSE`

R evaluate the relational expression `x <= y`

result to `FALSE, TRUE, TRUE, TRUE, TRUE`

. The relational expression `x >= 10`

result to `TRUE, TRUE, FALSE, TRUE, FALSE`

.

Later,it apply the logical AND (`&`

) on both the logical vectors,final result as `FALSE, TRUE, FALSE, TRUE, FALSE`

.

### Logical AND (`&&`

)

`x <= y && x >= 10`

`[1] FALSE`

In the above example, R evaluate the relational expression `x <= y`

result to `FALSE, TRUE, TRUE, TRUE, TRUE`

. The relational expression `x >= 10`

resulting to `TRUE, TRUE, FALSE, TRUE, FALSE`

.

Later, it apply the vector logical AND (`&&`

) on both the logical vectors,final result as `FALSE`

.

### Logical OR (`|`

)

`x >= y | x <= 12`

`[1] TRUE TRUE TRUE FALSE TRUE`

### Logical OR (`||`

)

`x >= y || x <= 12`

`[1] TRUE`

### Logical OR (`xor`

)s

`xor(x>=y,x<=12)`

`[1] FALSE TRUE FALSE FALSE FALSE`

Note that whenever we use logical operators on vectors of unequal length, R display a warning message and recycled the shorter vector to match the length of longer vector.

## Logical operations on Vectors of unequal length

When we use logical operations on vectors of unequal length, R display a warning message and recycle the elements of shorter vector to match the length of longer vector and then perform the logical operations.

### Logical NOT (`!`

)

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8)
! (x <= y)
```

```
Warning in x <= y: longer object length is not a multiple of shorter object
length
```

`[1] TRUE FALSE FALSE TRUE FALSE`

As vector `y`

is shorter than `x`

, R display the warning message but apply the recycling rule to make the length of `y`

similar to vector `x`

and execute the logical operations.

### Logical AND (`&`

)

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8)
x <= y & x == y
```

```
Warning in x <= y: longer object length is not a multiple of shorter object
length
```

```
Warning in x == y: longer object length is not a multiple of shorter object
length
```

`[1] FALSE FALSE TRUE FALSE FALSE`

First the elements of `y`

are recycled to match the length of `x`

. After applying the recycling rule, R evaluate the relational expressions `x <= y`

and `x == y`

and evaluate the logical expression.

### Logical AND (`&&`

)

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8)
x <= y && x == y
```

```
Warning in x <= y: longer object length is not a multiple of shorter object
length
```

`[1] FALSE`

### Logical OR (`|`

)

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8)
x <= y | x == y
```

```
Warning in x <= y: longer object length is not a multiple of shorter object
length
```

```
Warning in x == y: longer object length is not a multiple of shorter object
length
```

`[1] FALSE TRUE TRUE FALSE TRUE`

### Logical OR (`||`

)

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8)
x <= y || x == y
```

```
Warning in x <= y: longer object length is not a multiple of shorter object
length
```

```
Warning in x == y: longer object length is not a multiple of shorter object
length
```

`[1] FALSE`

### Logical exclusive OR (`xor`

)

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8)
xor(x <= y , x == y)
```

```
Warning in x <= y: longer object length is not a multiple of shorter object
length
```

```
Warning in x == y: longer object length is not a multiple of shorter object
length
```

`[1] FALSE TRUE FALSE FALSE TRUE`

## Logical operators for indexing

Logical operators are also used for selecting the elements of vector or data frame based on some logical conditions.

```
x <- c(12, 10, 8, 16, 6)
y <- c(10, 12, 8, 18, 6)
```

Suppose we need to extract only those elements of `x`

which are less than or equal to 10 and greater than or equal to 8. To do this we can use the logical condition `x <=10 & x >= 8`

as an index for vector `x`

.

`x[x <= 10 & x >= 8]`

`[1] 10 8`

Suppose we need to extract those elements of `x`

which are not equal to `y`

and `x < y`

. To do this we can use the logical condition `x != y & `

x < y` as an index for vector `

x`.

`x[x != y & x < y]`

`[1] 10 16`

## Endnote

In this tutorial you learned about logical operators in R and how R uses recycling rule while performing logical operations.

To learn more about other operators in R, please refer to the following tutorials:

Assignment operators in R

Arithmetic operators in R

Relational operators in R

Miscellaneous operators in R

Precendence of Operators in R

Operators in R

Hopefully you enjoyed learning this tutorial on logical operators in R. Hope the content is more than sufficient to understand logical operators in R.