Top R Programming Interview Questions and Answers

If you have an R programming interview coming up, congratulations! A job interview is your opportunity to shine and can be the first step toward an exciting new career. As you brush up on your interview skills and prepare, it’s also important to know some of the top R programming interview questions and answers. We’ve compiled a few of these commonly asked R programming questions, along with detailed advice on how to answer, so you can prove to your interviewer that you’re a perfect fit for the job.

10 R Programming Questions and Answers

1. Define R Programming. What Are Some of the R Functions That Exist?

You know what R programming is and does your interviewer, but he or she wants to hear you define it in your own words. This is why there’s a good chance this type of question will be part of your R programming questions. This seems like a simple R programming interview question, and in comparison, it may be, but the way you define R programming in your response can demonstrate the extent of your knowledge. Although you’ll want to answer that R programming is data analysis software, you may also want to explain who uses R programming - i.e. data scientists, data analysts, and so on.

Knowing R’s functions is an essential part of knowing R programming in general. While you may not be expected to list every single function that exists, listing as many as you can be optimal, memorize as many essential functions as you can - mean, median, distribution, etc. prior to your interview, in case this commonly asked question pops up.

2. What Can’t You Do with R Programming?

When it comes to demonstrating what you know about R programming and its capabilities, your interviewer may throw a curveball at you by asking what R programming isn’t capable of. Clearly, when it comes to any type of software, there is going to be an infinite list of what can’t be done, so it’s important to know what lack of features to focus on. Think about the things that a novice R programming user might mistakenly think that the software is capable of. For example, a new data scientist might think that with R programming, you can view data in a spreadsheet. This is a good example of a feature not available through R programming and would be a good one to mention. New users might also mistakenly think R is a database or that it may contain a graphical user interface; these are two other features that are not included in R programming and would be good to include in your response. When you give these answers, be sure to explain why you specifically chose them.

3. In the R Programming Language, How Are Missing Values and Impossible Values Represented?

Aside from telling the interviewer exactly how these two values are represented in R programming (NA for missing values and NaN for impossible values), you should also briefly explain what these two values mean and why a user might encounter them. You should also explain that while some users may be tempted to just delete missing values and move on, it ’s ideal to try and uncover the primary cause of these erroneous values. Because there could be a flaw somewhere in the programming, finding and fixing this root cause can potentially prevent similar mistakes from popping up later on.

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4. How Do You Solve a Problem in R?

The solutions available are referred to as “packages” in R, so be sure to use this term in your answer. First, explain that the CRAN package ecosystem has an extensive amount of packages available (over 6,000) to solve potential issues. Each R user might have their own way of making their selection, but the best way to answer this question is to explain how reviews from others go a long way: Were other R users with similar issues able to solve their problems with a particular package? If so, were these issues similar to the problems you’re encountering? In your answer, explain that you’d be wary of packages that don’t encompass good software development principles, have poor reviews, or are lacking reviews altogether.

5. What Objects Do You Use Most Often in R?

Your interviewer wants to get a sense of how experienced you are in R programming with this question. Be prepared by knowing, in detail, some of your recent work and explain your most frequently used objects, while also explaining how and why you use them.

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6. Can You Write a Specific Code to Accomplish a Task?

Interviewers will likely want to see you demonstrate that you know how to code when you’re interviewing for an R programming job. While you can expect a lot of questions that will test your knowledge and experience, nothing can demonstrate your skills in R quite like actually showing the interviewer what you can do. 

Because you should be prepared for this type of hands-on question, be prepared before your interview to write code that can accomplish a specific task. You may be asked to write a specific type of code, or you may have the choice to choose your own. You should not only have some of the basics memorized but in case you’re given the freedom to choose what you want, be sure to choose something you’re comfortable with. After all, it can be a little nerve-wracking to be asked to code right there on the spot and during an interview.

Although you’ll want to be prepared with something you know inside and out, don’t be too afraid to step out of your comfort zone, either. You’ll likely get bonus points if you can perform a specific task that is somewhat challenging and will impress your interviewer.

7. How Is R Similar to Python? How Are the Two Different?

This is your interviewer’s way of seeing that you are familiar with other types of programming and coding language, and not just R. If R is the only programming language you’re familiar with, you may want to familiarize yourself with others just in case you’re asked to compare and contrast the two, which is likely. Even if you don’t know Python as well as R, you can stick to some of the basics: i.e. for similarities, they both have strong modeling capabilities and they are both free to use. As far as differences, you can point out that although many software programmers feel that Python tends to be easier to use and is more secure, R is better for those who appreciate visualization tools.

8. What Are Some of the Pros and Cons of R?

With just about any program out there, there are going to be advantages and disadvantages. Your interviewer is not necessarily looking for all of the pros and cons, nor is he or she necessarily expecting you to name specific features. Your interviewer is just using this as another question to test the extent of your knowledge, so be sure to know some pros and cons before heading into your interview. For example, you can say that many programmers like R because it’s free, widely accessible, and has built-in functionality via R packages. For disadvantages, you may want to point out that there are some security flaws, and that it is also open-source, which some people even consider a disadvantage. Keep it simple by thinking about what you personally like about R, and what you don’t.

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9. What Are Some of Your Favorite R Programming Functions?

If you’re interviewing for a job in R programming, it’s not just important that you understand and know R inside and out, but that you’re passionate about it, too. Your interviewer should expect that as an expert in R, you’ll not only be able to easily come up with functions on the spot but that you can easily name the ones you like the most (and why). Be sure to answer this question with confidence and enthusiasm. 

10. How Many Data Structures Are Available in R Programming?

It’s important not just to answer this question with a number, but also explain what these structures are and what they include. Tell your interviewer that there are two data structures: homogeneous and heterogeneous. When responding to this question, also mention that homogeneous data structures include the same type of objects: array, matrix, and vector. Heterogeneous data structures include different types of objects: data lists and frames.


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About the Author

Shardul Prakash MohiteShardul Prakash Mohite

Shardul heads Product Management at Simplilearn. He has over 10+ years of entrepreneurial experience in building products for international markets in domains such as education, video, and sports. Prior to this role, Shardul was a co-founder at a SaaS-based video-tech startup. He believes in first-principle thinking and is a life-long student of human behavior, user experience, data-driven decision making, and lean thinking. Shardul is a computer engineering graduate from Pune University, India. He is an avid reader, enjoys long drives and travel.

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