The post is about another data structure called Vectors in R Programming. It is in the form of questions and answers with examples. Here we will discuss some important vector functions, recycling of elements, and different types of vectors with examples.
What are Vectors in R Programming?
Vectors in R Programming are basic data structures. It comes in two parts: atomic vectors and lists (recursive vectors). A vector in R language is a fundamental data structure that stores a collection of elements, all of the same data type (like numbers, characters, or logical values). Vectors in R Programming are essentially one-dimensional arrays.
How many types of vectors are in R?
The primary types of vectors in R Programming are
- Logical Vectors (stores TRUE or FALSE values)
- Integer Vectors (Stores Whole numbers, i.e., integers only)
- Double (Numeric) Vectors (Stores decimal numbers)
- Character Vectors (Stores text strings)
The less common types of vectors are:
- Complex Vectors
- Raw Vectors.
How to Create Vectors in R Programming Language?
To create vectors in R Programming Language, the following are few ways:
- Create a vector using integers, use the colon (
:) operator. For Example, typing 2:6 results in a vector with numbers from 2 to 6, and typing 3:-4 creates a vector with the numbers 3 to -4.
- Create a vector using the
seq() Function, Write a command such as seq(from = 4.5, to = 3.0, by = -0.5) to create a vector of numbers from 4.5 to 3.0 by decrementing 0.5 step, that is, 4.5 4.0 3.5 3.0.
- The
seq() function may also be used by specifying the length of the sequence by using the argument out, e.g., seq(from = -2.7, to = 1.3, length.out = 9). It will result in -2.7 -2.2 -1.7 -1.2 -0.7 -0.2 0.3 0.8 1.3.
What are Logical Vectors in R Programming?
In R language, a logical vector contains elements having the values TRUE, FALSE, and NA. Like numerical vectors, R allows the manipulation of logical quantities.
What are Vector Functions?
In R language, some functions are used to perform some computation or operation on vector objects, for example, rep(), seq(), all(), any(), and c(), etc. However, the most common functions that are used in different vector operations are rep(), seq(), and c() functions.
How One Can Repeat Vectors in R?
One can use the rep() function to repeat the vectors. For example, to repeat a vector: c(0, 0, 7), three times, one can use rep(c(0, 0, 7), times = 3).
To repeat a vector several times, each argument can be used, for example, rep(c(2, 4, 2), each = 2).
To repeat each element, and how often it has to repeat, one can use the code, rep(c(0, 0, 7), times = 5)
The length.out argument can be used to repeat the vector until it reaches that length, even if the last repetition is incomplete. For example, rep(1:3, length.out = 9).
rep(c(0, 0, 7), times = 3)
rep(c(2, 4, 2), each = 2)
rep(c(0, 0, 7), times = 5)
rep(1:3, length.out = 9)
What is the Recycling of Elements in R Vectors?
When two vectors of different lengths are involved in an operation then the elements of the shorter vector are reused to complete the operation. This is called the recycling of elements in R vectors. For example,
v1 <- c(4, 1, 0, 6)
v2 <- c(2, 4)
v1 * v2
## Output
8, 4, 0, 24
In the above example, the elements 2 and 4 are repeated.
What do copy-on-change Issues in R?
It is an important feature of R that makes it safer to work with data. Let us create a numeric vector x1 and assign the values of x1 to x2.
x1 <- c(1, 2, 3, 4)
x2 <- x1
Now x1 and x2 vectors have exactly the same values. If one modifies the element(s) in one of the two vectors, the question is do both vectors change?
x1[1] <- 0
x1
## Output
0 2 3 4
x2
## Output
1 2 3 4
The output shows that when x1 is changed, the vector x2 will remain unchanged. It means that the assignment automatically copies the values and makes the new variable point to the copy of the data instead of the original data.
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