Most asked top Interview Questions and Answers & Online Test
Education platform for interview prep, online tests, tutorials, and live practice

Build skills with focused learning paths, mock tests, and interview-ready content.

WithoutBook brings subject-wise interview questions, online practice tests, tutorials, and comparison guides into one responsive learning workspace.

Prepare Interview

Mock Exams

Make Homepage

Bookmark this page

Subscribe Email Address
Home / Interview Subjects / R Language
WithoutBook LIVE Mock Interviews R Language Related interview subjects: 9

Interview Questions and Answers

Know the top R Language interview questions and answers for freshers and experienced candidates to prepare for job interviews.

Total 30 questions Interview Questions and Answers

The Best LIVE Mock Interview - You should go through before interview

Know the top R Language interview questions and answers for freshers and experienced candidates to prepare for job interviews.

Interview Questions and Answers

Search a question to view the answer.

Intermediate / 1 to 5 years experienced level questions & answers

Ques 2

What is the purpose of the 'merge()' function in R?

The merge() function is used to merge two or more data frames based on a common column.

Example:

merged_data <- merge(df1, df2, by='common_column')
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments
Ques 3

Explain the concept of factor variables in R.

Factor variables are used to represent categorical data in R. They can have levels, which represent the categories.

Example:

gender <- factor(c('Male', 'Female', 'Male'), levels=c('Male', 'Female'))
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments
Ques 4

How do you handle missing values in a data frame in R?

You can use the na.omit() function to remove rows with missing values, or use functions like is.na() to identify missing values.

Example:

cleaned_data <- na.omit(df)
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments
Ques 5

Explain the purpose of the 'dplyr' package in R.

The 'dplyr' package provides a grammar of data manipulation, with functions like filter(), select(), and mutate(), making data manipulation tasks more intuitive.

Example:

library(dplyr)
filtered_data <- filter(df, Age > 25)
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments
Ques 6

Explain the purpose of the 'purrr' package in R.

'purrr' is a package in R that enhances functional programming with a consistent and concise syntax, making it easier to work with lists and vectors.

Example:

library(purrr)
map(my_list, my_function)
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments
Ques 7

What is the purpose of the 'reshape2' package in R?

'reshape2' is a package used for reshaping data frames. It provides functions like melt() and cast() for converting between wide and long formats.

Example:

library(reshape2)
melted_data <- melt(my_data, id.vars=c('id', 'name'))
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments
Ques 8

How do you handle exceptions in R?

You can use the 'tryCatch()' function to handle exceptions in R. It allows you to define code to be executed in case an error occurs.

Example:

tryCatch({
  # code that might cause an error
}, error = function(e) {
  # code to handle the error
})
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments
Ques 9

Explain the purpose of the 'caret' package in R.

'caret' is a package in R used for streamlining the process of applying machine learning models. It provides a unified interface for various modeling techniques.

Example:

library(caret)
model <- train(y ~ ., data = my_data, method = 'lm')
Save For Revision

Save For Revision

Bookmark this item, mark it difficult, or place it in a revision set.

Open My Learning Library
Is it helpful?
Add Comment View Comments

Most helpful rated by users:

Copyright © 2026, WithoutBook.