How to Construct Vectors in R, What is a vector

How to Construct Vectors in R What is a vector? Vectors are the most fundamental data structure in R. They can be used to represent a wide range of different types of data, such as numbers (for example, 1, 2 and 3), characters (such as “A”, “B” and “C”), or even more complex objects like lists and matrices.

Learning how to use vectors is an essential skill for anyone who wants to start working with R. However, there seems to be a lot of confusion about what exactly vectors are in R programming language!

In this post I will explain everything you need to know about vectors in R including how they work behind the scenes as well as their pros and cons compared with other types of data structures available in the programming language.

in R what is a vector
in R what is a vector?

In R What is a vector?

in R what is a vector? Vector is a single entity with two or more components. For example, we can say that the vector ‘x’ has x = (1, 2) and y = (3, 4). These are individual components which make up the whole vector. Vectors in R can be used as inputs to other commands such as loops and if statements, creating logical decisions with the data.

How to create vector in R??

There are multiple ways to create vectors in R; some of which can be done without writing a single line of code. The simplest way is the c() function, where you write the values of your vector inside and seperate them with a comma. For example: v <- c(9, 10, 11) would create a vector named ‘v’ with four values: 9, 10, 11 and NA (Not Available). Another way is to use the vector() function, which will require you to manually input the values. For example: v <- vector(c(9, 10, 11), length = 4) would give us the same result as above.

How to create vector in R??
How to create vector in R??

How to access Elements of a Vector?

How to access Elements of a Vector?
How to access Elements of a Vector?

There are two ways to access Elements of a Vector.

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First is by using the command c() and passing it as an input. For example, we can say y = c(3, 4) and then use the following syntax:

y <- 3+4

This will add up three and four and store that result in variable y.

Second is by using the command which() and passing it as an input with the Vector we want to access. For example, we can say vectorA = c(1:10) and then use the following syntax:

which (vectorA == 5)

This will tell us what position number 5 exists in vectorA, if it exists.

How to modify a vector in R?

There are two ways to modify a vector in R.

First is by using the command c() and passing it as an input. For example, we can say y = c(3, 4) and then use the following syntax:

y <- y+5

This will add 5 to variable ‘y’, making y equal 8.

Second is by using the command which() and passing it as an input to another vector with the position number of where you want to insert data. For example, we can say vectorA = c(1:10) and then use the following syntax:

y <- c(y, which (vectorA == 8))

This will take the existing position number of data in vectorA, which is 8 and add that to the variable y. This would make y equal 13.

Is there a way to find the second largest number in a vector using R?

Yes, we can easily use the which() function. This is an extremely useful function as it gives you all of the positions of elements that are equal to what you pass as an argument.

For example, let’s say I wanted to find out the position of the second largest number in a vector. We could use the following syntax:

which (x == x [2])

This would give us all of the positions that are equal to element 2 in our vecotr, which is 6 and 7.

So now we have this function, let’s say I have the following vector:

vecA = c(1,2,3,4)

This is what our output would look like if we ran the following code:

which (x == x [2])

6 7

Since both element 6 and 7 are equal to 2 in the vector vecA, they will return as our output.

Now, let’s say that we want to find the second smallest number instead of the second largest. This is extremely easy as well and we can do it by changing which() to smalldat() like this:

smalldat (x == x [2])

4 5

Here, element 4 and 5 are both equal to 2 in the vector vecA, so they will return as our output.

As you can see, it is very easy to change which() into smalldat() and use it to find second largest or second smallest numbers in a vector.

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How to delete a Vector?

There are two ways to delete a Vector.

First is by using the command c() and passing it as an input. For example, we can say y = c(3, 4) and then use the following syntax:

del(y)

This will delete variable ‘y’ from memory. It is extremely important to note that this does not delete the data itself, but instead removes it from your current session. If you want to remvoe the data as well, use rm(y).

Second is by using the command which() and passing it as an input with a Vector of the elements that you want to remove. For example, we can say vectorA = c(1:10) and then use the following syntax:

del (which (vectorA == 9))

This will tell us all of the position numbers that are equal to element 9 in vectorA, which is 3 and 4. We would then pass this to the del() command as an argument, effectively removing positions 3 and 4 from the vector. This has the effect of removing element 9 from our vector because positions 3 and 4 are equal to 9.

Repeating Vectors

R can repeat a vector many times, by using the ‘rep()’ command. This is often used in for loops where we wish to iterate over a set of data multiple times.

You can use the ‘ rep() function in several ways. rep()’ command to generate replicate vectors of any length.

How do Functions work?

If you want to generate a vector of 100 zeroes, the following would be an example of how this can be done:

z<-rep(0,100)

By executing this code in the console, we get the desired result. The command ‘ z <- rep(0,100)’ has assigned the vector ‘0’ to the variable ‘z’. This is because the vector ‘0’ has repeated itself 100 times.

R Tutorial

Using integer vector as index

R is a programming language for statistical computation and graphics providing a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques. This tutorial covers the basics of R programming from setting up environment to using various features of R.

Vectorization in statistics refers to the process of replacing traditional scalar operations with the operations performed on entire vectors. In Julia, a single element can hold an arbitrary number of values, and it is thus possible to perform all manner of vectorized computations. This means that each iteration is computed in parallel, while still having a very simple syntax that applies to every type.

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There are a number of reasons why you might want to delete a Vector. Most commonly, it is because the vector’s elements are troublesome or incorrect. However, if you have created a vector by accident, then deleting the vector will remove the data from memory and release that memory for reuse. Deletion can also be useful if you want to rerun a particular part of an analysis or if you have a step that you want to skip during the course of your data analysis.

Using logical vector as index

In computer science, a vector is a sequence of data elements, measured in terms of number of elements n-1. Vectors are known to have many applications in real world problems due to their extensive use in statistics and machine learning. R provides the same functionality using its built-in package ‘vectors’.

FAQ

What does vector () do in R?

Vector () is an R command that creates a Vector, which is an ordered list of elements, typically numbers or text entries. You can create vectors by using literal values or by providing numerical index values for accessing individual elements in a vector of data. You can extract parts from a vector by using negative index values.

Is everything a vector in R?

There is a special built-in type of vector called a factor in the R programming language. Everything else in R is essentially considered to be a vector, although not always explicitly declared as such.

Is a vector a data structure?

Vectors are one of the most commonly used data structures in R. A vector is an ordered list of elements, typically numbers or text entries. They are indexed starting with 1, unlike Python lists which start with 0.

What is difference between vector and list?

Vector and list are two different implementations of the same abstract data type. A vector is a list with an index starting at 1. list() creates lists that can be indexed from 0, whereas Vector() creates lists that can be indexed from 1.

How do I input a vector in R?

There are multiple ways to create a vector in R. You can use the c() function to combine a list of elements into a single vector, or you can manually assign column vectors using matrix().

Conclusion

Vector is a construct of the R programming language. It is an ordered list of elements, typically numbers or text entries, with each element being assigned an index number for referencing it on an individual basis. Vectors are used in many statistical functions and data analysis procedures to encode data into manageable, structured forms.

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