Remove Last Value From a List in R - Data Science Parichay

In this tutorial, we will look at how to remove the last value from a list in R with the help of some examples.

How to remove the last value in a List in R?

You can remove the last value from a list in R by setting the value at the last index (same as the list’s length) to NULL. You can use the length() function to get the length of a list in R. The following is the syntax –

# remove last value from list
ls[length(ls)] <- NULL

You can also use the above syntax to remove any value from a list using its index. Just replace length(ls) with the index of the value you want to remove from the list.

Examples

Let’s look at some examples of removing the last value from a list in R.

First, let’s create a list with four values and remove the last value using the syntax mentioned above.

Highlighted programs for you

Put simply, All Star is in the business of connecting students and schools. We help students find schools that are great matches for their educational needs, personal preferences and lifestyles, and schools pay us for our work.

Here's a quick Q & A of information we think you should know if you choose to use our websites. The main takeaways: Using our services is free, but starting and completing a degree, certificate or diploma program takes commitment and effort and should be considered carefully.

1. How do you provide your services for free?

Schools pay to advertise on our sites. This allows us to offer our service to prospective students like you for free.

Schools place a very high priority on enrolling students who go on to graduate. By using All Star's focused, information-rich services, schools can be more confident that the prospective students we introduce them to are truly committed to their education and to succeeding once they're enrolled in school.

2. How do you differ from your competitors?

There are other companies out there that do what we do. But there is no one that does it with more integrity or respect for our users and their choices. We put you, the student, in control. You get to choose the schools you're interested in, and you get to choose what programs you'd like to learn more about. We will never submit your contact information to a school without your consent.

3. Do you really work with ALL schools?

No. Our listings are not exhaustive, we do not list all schools, but they do include a rich selection of options. We believe this wide variety of options from hundreds of schools meets the needs of most prospective students who visit our sites. We partner with smaller schools that specialize in one particular career field, such as Pima Medical Institute, as well as world-class, multi-discipline institutions like the University of Southern California.

4. Is getting a degree really going to open up doors for me?

We really want you to succeed in the program you choose. So does your school. But we feel compelled to be very frank and upfront: You must work hard and stay committed to graduate. And assuming you do graduate, there is no guarantee you will find a job in your chosen field, or any job for that matter.

Obtaining an education has many personal benefits and can also improve your financial prospects. However, it's important to keep in mind that obtaining an education does not guarantee financial success or even a job. Job markets vary greatly by region, state, and even locally, and are affected by trends in the national economy and even international events. Other factors affecting your job-hunting success may include your job history and experience, and your level of education, degree, or certificate type. Your area of specialization plays a role, too.

5. If I do find a job, what can I expect in terms of salary?

The government publishes a great deal of information related to hundreds of jobs on the Bureau of Labor Statistics (BLS) website. We use this as a resource for many of the articles on the All Star websites. As comprehensive as the BLS information is, it is neither complete nor entirely accurate. The BLS salary information we publish is a national average. Actual salaries for a particular job or skill may be different where you live. For example, if you live in a large city or where the job market for particular skills is especially competitive, such as Silicon Valley in California, you're likely to receive a higher wage or salary for the same job than you would in a rural or economically depressed market. Other factors that can affect salary rates include the size of the employer, union contracts and governmental regulations to name a few.

6. Where are you located? How can I contact you?

All Star Directories is located at P.O. Box 1677 Renton, WA 98057. You can reach us at (206) 436-7500 or at customerservice@allstardirectories.com.

Flatiron School

Data Science Bootcamp

Product Design UX/UI Bootcamp

University of Maryland Global Campus

Cloud Computing Systems Master's

Digital Forensics & Cyber Investigation Master's

Creighton University

Health Informatics Master's

# create a list
ls <- list("a", "b", "c", "d")
# remove the last element
ls[length(ls)] <- NULL
# display the list
print(ls)

Output:

[[1]]
[1] "a"

[[2]]
[1] "b"

[[3]]
[1] "c"

Here, we create a list of four character values and then set the value at the last index in the list (which we get using the length() function) to NULL. We then print the list. You can see that the list now does not have the last value from the original list.

Alternatively, you can use negative indexing to exclude values at certain indexes (for our use case, remove the last value). Note that this does not modify the list in place. To modify the original list, assign the result from the negative indexing to the original list variable.

Let’s remove the last element from the same list used in the example above. A list of four character values.

# create a list
ls <- list("a", "b", "c", "d")
# remove the last element
ls <- ls[-length(ls)]
# display the list
print(ls)

Output:

[[1]]
[1] "a"

[[2]]
[1] "b"

[[3]]
[1] "c"

You can see that we get the same result as above.

Author

Piyush Raj

Piyush is a data professional passionate about using data to understand things better and make informed decisions. He has experience working as a Data Scientist in the consulting domain and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.

View all posts