Sometimes you may want to create empty vector in r as a placeholder. Such a placeholder has the advantage that it will not create an error message if it is referred to before any data is added to it. It is a convenient way to fix an “object not found” error message when you are not ready to add actual data to the vector.

### Description of The Process

When you create an empty vector in r you have several functions from which you can choose. Each function produces slightly different results. The main difference is the class that the vector is assigned. The functions are the vector, character, numeric, logical, integer, complex, factor, double, raw, and rep functions. In this situation, they each have the format of vector(), character(), numeric(), integer(), complex(), factor(), double(), raw(), and rep(NA, times) where times equals the number of times the missing value is repeated. The vector and rep functions produce empty logical vectors, while the others produce empty vectors of their respective types. It is a straightforward process, with the only complication being the fact that there is more than one way to produce an empty vector.

### How This Works in Practice

You create an empty vector in r by applying a create vector function that does not have even a single data element in it. An empty vector is the simplest possible r vector, they also qualify as an atomic vector. Furthermore, if you use empty vectors as the columns for a data frame, the result is an empty data frame. Unless the vector holds missing values, an empty vector will have a length of zero. On the other hand, a vector holding missing values can have any length and still qualify as an empty vector. Empty vectors are essentially a placeholder for the vector name, making it a handy tool for avoiding error messages.

### Examples: How to Create an Empty Vector in R

Here are four examples of how to create an empty vector in r. Each one shows a different approach to making an empty vector.

> x = vector()

> x

logical(0)

> length(x)

[1] 0

> class(x)

[1] “logical”

> x = c(x, 1:10)

> x

[1] 1 2 3 4 5 6 7 8 9 10

> x = c(x, “A”, “B”, “C”, “D”, “E”, “F”, “G”)

> x

[1] “1” “2” “3” “4” “5” “6” “7” “8” “9” “10” “A” “B” “C” “D” “E” “F” “G”

In this example, we initialize empty vector using the vector function. The result is an empty logical vector.

> x = character()

> x

character(0)

> length(x)

[1] 0

> class(x)

[1] “character”

> x = c(x, 1:10)

> x

[1] “1” “2” “3” “4” “5” “6” “7” “8” “9” “10”

In this example, we initialize an empty vector using the character function. This process produces empty character vectors.

> x = integer()

> x

integer(0)

> length(x)

[1] 0

> class(x)

[1] “integer”

> is.atomic(x)

[1] TRUE

> x = c(x, 1:10)

> x

[1] 1 2 3 4 5 6 7 8 9 10

In this example, we initialize an empty vector using the integer function. The result is an empty integer vector.

> x = rep(NA, times=10)

> x

[1] NA NA NA NA NA NA NA NA NA NA

> length(x)

[1] 10

> class(x)

[1] “logical”

> x = c(x, 1:10)

> x

[1] NA NA NA NA NA NA NA NA NA NA 1 2 3 4 5 6 7 8 9 10

> x = c(1:10)

> x

[1] 1 2 3 4 5 6 7 8 9 10

In this example, we initialize an empty vector using the rep function along with missing values. The result is an empty logical vector with missing values. Even though this vector has missing values, it still qualifies as an empty vector because a missing value does not qualify as a value. As a result, if you are using empty values, you can have an empty vector that has a length.

### Applications: Creating an Empty Vector in R

The main application of an empty vector in r is as a placeholder for the vector name. This has the advantage that it easily prevents the “object not found” error message from occurring even if you have not added any values to the vector. An empty vector is still an R object and therefore you will not get an “object not found” error message. Another useful application for creating an empty vector is the situation where you are using a for loop to build up the contents of a vector. This procedure may be necessary if you must calculate the values one at a time. This would be particularly true if you are using an algorithm where the next value is dependent upon the previous value. When using a for loop you built the vector by using the c function with the vector you are building as the first argument as shown in the earlier examples.

When you create an empty vector in r there are several ways that you can do it. Each of them results in different data types. However, only in the case where the vector uses missing values does it have a length. In all other cases, they have a length of zero. This makes them useful not only as placeholders but as starting points for a for loop that will build up the vector one element at a time.