R Interview Questions and Answers

Last updated on Jul 15, 2020
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R Interview Questions

R is a robust programming language and software environment used for statistical analysis, graphical representation, and reporting. It is a well-structured, efficient, and straightforward programming language that includes loops, conditionals, user-defined recursive functions, input, and output facilities.

Read our list of r interview questions to get yourself updated on this language which provides an efficient data handling, storage facility, and a suite of operators for various calculations on arrays, vectors, and matrices.

Besides calculation and statistics, R provides a coherent, extensive, and integrated collection of various data analysis tools. Read the r interview questions to understand how R provides graphical facilities for data analysis and presentation on paper or digitally.

R is the world's most widely used statistics programming language. It's the first choice of data scientists and supported by a range of talented community contributors. It is taught in many universities and is also deployed in mission-critical business applications. This tutorial will give you the most commonly asked r interview questions along with relevant examples in simple and clear steps.

Most Frequently Asked R Interview Questions

Here in this article, we will be listing frequently asked R Interview Questions and Answers with the belief that they will be helpful for you to gain higher marks. Also, to let you know that this article has been written under the guidance of industry professionals and covered all the current competencies.

Q1. What are the features of R programming?
Here are the features of R Programming:
  • It is free, open-source, and can be adjusted according to a user's project requirements.
  • It has a highly active and growing community, which helps beginners gain support to learn this language.
  • R is basically an Object Oriented Programming language which consists of a versatile package called Rshiny which can be used to make full-fledged Web apps.
  • R has packages like ddR and multiDplyr, enabling it to use distributed computing for handling large data sets.
  • R is an interpreted language, meaning it does not require a compiler to execute its code.
Q2. What is the use of R markdown?

R Markdown is a file format that is used for making dynamic documents within R.

Did you know?

R was initially written by Robert Gentleman and Ross Ihaka at the Department of Statistics at the University of Auckland, New Zealand. R made its first public appearance in 1993. Read our list of r programming interview questions to get acquainted with this language.

Q3. What is cbind and rbind in R?

Cbind in R is a function that stands for column-bind. It is used for combining vectors, matrices, and data frames by columns.


cbind(data_input, new_column)

On the other hand, Rbind is a function in R that stands for row binds. It is used to bind the data frames by doing a simple joining or concatenation of two or more tables row-wise.



Q4. How does random forest work in R?

Random forests in R programming work in the same fashion as decision trees. It combines all the output from the multiple decision trees and comes up with its output. However, one significant difference from decision trees is that it does not select all the variables and data points in each tree. It just randomly selects and samples variables from each tree and then combines the output.

Q5. What does the subset function do in R?

The subset function in R is used for multiple purposes such as:

  • Returning subsets of a vector, matrix, or data frame which meeting a particular condition
  • Selecting specific elements of a data structure.
Q6. What is plots in R?

Plots in R are a useful tool whose main purpose is to help in graphically presenting data. It can be used to display, compare, composition, distribution, and relationships between variables and data points.

Plots can be of 6 types:
  • Histogram
  • Heatmaps
  • Correlogram
  • Scatterplot
  • Box plot
  • Bar/Line Chart

Note: R's core is actually an interpreted computer language allowing the branching and looping along with modular programming using functions. Read more of our r interview questions to understand the core of this language and its workings

Q7. What does GSUB do in R?

The GSUB is a function in R is used to replace all matches of a string. If the parameter is a string vector, it returns a string vector with the same length and attributes.

Q8. What is the use of with () and by () function in R?

The with() function in R is used to perform expressions using the variables inside a list or data frame. The with function will also keep track of any changes made, which includes adding or deleting elements and returning a new object with revised contents.

The by() function in R is used to apply a function to some specified subsets within a data frame.


by(data, data$byvar, FUN) data$byvar: It is a factor or a list of factors on which the function is applied
FUN: Is a function that is applied to the subsets of data.

Q9. What are the different type of sorting algorithms available in R language?

There are 5 types of different sorting algorithms present in R programming. They are:

  • Bucket Sort
  • Merge Sort
  • Bubble Sort
  • Quick Sort
  • Selection Sort
Q10. How do you match a string in R?

To match a string with some parameters, the grep() function is used. The grep() function returns the index at which the pattern is found in the string. It also tells us the location of the specified string in the vector.


Find all the instances of 'he' in the string.

str <- c("Hello", "hello", “human”, "hi", "hey")
grep('he', str)


[1] 1 2 5

Note: R allows various integration with its procedures written in the C, C++, .Net, Python, or the FORTRAN languages for efficiency. Read answers to the r coding interview questions carefully to understand the subject and get that dream job.

Note: R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests,) and also graphical techniques, which is highly extensible. Read our list of r programming interview questions to get better in this language and even start working on your own data science project!

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