Register for our webinar

How to Nail your next Technical Interview

1 hour
Loading...
1
Enter details
2
Select webinar slot
*Invalid Name
*Invalid Name
By sharing your contact details, you agree to our privacy policy.
Step 1
Step 2
Congratulations!
You have registered for our webinar
check-mark
Oops! Something went wrong while submitting the form.
1
Enter details
2
Select webinar slot
*All webinar slots are in the Asia/Kolkata timezone
Step 1
Step 2
check-mark
Confirmed
You are scheduled with Interview Kickstart.
Redirecting...
Oops! Something went wrong while submitting the form.
close-icon
Iks white logo

You may be missing out on a 66.5% salary hike*

Nick Camilleri

Head of Career Skills Development & Coaching
*Based on past data of successful IK students
Iks white logo
Help us know you better!

How many years of coding experience do you have?

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Iks white logo

FREE course on 'Sorting Algorithms' by Omkar Deshpande (Stanford PhD, Head of Curriculum, IK)

Thank you! Please check your inbox for the course details.
Oops! Something went wrong while submitting the form.

Help us with your details

Oops! Something went wrong while submitting the form.
close-icon
Our June 2021 cohorts are filling up quickly. Join our free webinar to Uplevel your career
close
blog-hero-image

Python Data Science Interview Questions You Need to Prepare

by Interview Kickstart Team in Interview Questions
November 20, 2024
Learn from FAANG Data Scientists and nail your next interview!

Python Data Science Interview Questions You Need to Prepare

Last updated by Dipen Dadhaniya on Aug 30, 2024 at 05:45 PM | Reading time: 8 minutes

You can download a PDF version of  
Download PDF

If you’re looking to build a career in data science, you already know how important Python will be. The significance of Python data science interview questions at interviews has risen exponentially. After all, it is the most widely used language in data science.

When preparing for a data science Python interview, you’ll need to cover all of the major Python concepts so that you’re fully prepared to answer any Python data science interview questions that come your way.

In this article, we cover the commonly asked Python data interview questions. We also give some sample questions that you might be asked during the interview.

Python Data Science Interview Questions and Answers

As you prepare for the Python data science interview questions, keep the following in mind and prepare accordingly. According to our observations, these questions have helped software engineers nail their tech interviews:

Q1. What is Python, and What is it Used for?

An interpreted high-level, general-purpose programming language, Python is often used in building websites and software applications. Apart from this, it is also useful in automating tasks and conducting data analysis. While the programming language can create an array of programs, it hasn’t been designed keeping in mind a specific problem(s).

Q2. List the Important Features of Python.

Some significant features of Python are:

  • It supports structured and functional programmings
  • It developed high-level dynamic data types
  • It can be compiled to byte-code for creating larger applications
  • It uses automated garbage collection
  • It can be used along with Java, COBRA, C, C++, ActiveX, and COM

Q3. What are the Different Built-In Data Types in Python?

Python uses many built-in data types.

Q4. Explain How Python Data Analysis Libraries are Used and List Some Common Ones.

The collection of data analysis libraries used in Python includes a host of functions, tools, and methods that manage and analyze data. Some of the most popular Python data analysis libraries are:

Q5. What is a Negative Index Used for in Python?

You can answer this Python data science interview question by stating that the negative indexes in Python are used to assess and index lists and arrays from the end, counting backwards. For instance, n-1 shows the last time in a list while n-2 shows the second to last.

Q6. What Does it Mean When We Say that Python is an Object-Oriented Language?

When we say Python is an object-oriented language, we mean that it can enclose codes within the objects. When the property permits the storage of the data and the method in a single unit, it is known as the object.

Q7. Explain a Python Module. What Makes it Different from Libraries?

A single file or many files containing functions, definitions, and variables created to perform certain tasks is called a module. It’s a .py extension file that can be imported at any given point and needs to be imported just once.

A library is a collection of reusable functionality of code that’ll allow users to carry out a number of tasks without having to write the code. A Python library doesn’t have any specific use but refers to a collection of modules.

This question is one of the most popular Python data science interview questions.

Q8. What is PEP8?

You can answer this Python data science interview question by stating that coding convection PEP8 contains coding guidelines. These are a set of recommendations put together for the Python language that make the language more readable and easy to use for users.

Q9. Name Some Mutable and Immutable Objects

The ability of a data structure to change the portion of the data structure without needing to recreate it is called mutability. At the same time, immutability is the state of the data structure that can’t be tampered with after its creation.

Q10. What are Generators and Decorators?

You can answer this Python data science interview question by stating that the generator function is responsible for simplifying the process of creating an iterator. A decorator manipulates pre-existing functions or their output, which it does by adding, deleting, or altering characteristics. 

Q11. Differentiate Between %, /, and //?

You can answer this Python data science interview question by describing the following differences:

Q12. What is the Lambda Function?

The following are some of the key Lambda functions:

  • Lambda functions are anonymous as they aren’t declared in the standard manner using the def keyword. Further, it doesn’t even need the return keyword. Both are implicit in the function.
  • These functions have their local namespace and don’t have any access to variables other than those in their perimeter list and those in the global namespace.
  • Examples: x = lambda i,j: i+j

print (x(7,8))

Output: 15

Yet another important question in this list of Python data science interview questions. So prepare accordingly.

Q13. Explain the Map, Reduce and Filter Functions.

The following table can help you learn &  answer this Python data science interview question:

Q14. What is the Difference Between Range, Xrange, and Arange?

The difference between range(), xrange() and arange() is as follows:

Q15. How do you Differentiate Between Global and Local Variables?

You can answer this Python data science interview question by describing the following differences:

Sample Python Data Science Interview Questions for Practice

As you dig deeper and prepare for Python data science interview questions, do practice the following questions as well:

16. Differentiate between lists and tuples in Python.

17. What are positive and negative indices?

18. Define Pass statement in Python.

19. What are the limitations of Python?

20. Give an example of runtime errors in Python.

21. What is meant by compound data types and data structures?

22. Explain with an example what list and dictionary comprehension are.

23. Define tuple unpacking. Why is it important?

24. Differentiate between is and ‘==’

25. How do you differentiate between indexing and slicing?

26. Explain zip() and enumerate() function.

27. What is a default value?

28. What’s the role of namespaces in Python?

29. What is Regex? List some of the important Regex functions in Python.

30. Differentiate between pass, continue and break.

Master Python Interview with Interview Kickstart

Python is one of the most widely used programming languages in the world. It is used in several applications such as machine learning, data science, and more. Interview Kickstart is a leading name in helping people chase and achieve their dreams of getting into tech jobs.

Its Machine Learning course will teach you about mathematical and machine learning concepts, and prepare you for system design and data structure & algorithm-based interviews.

The data science course will prepare you to master data science concepts like data wrangling, data analysis, big data analysis, data visualization, and more. 

These courses, at Interview Kickstart, are taught by instructors with experience of working in FAANG+ companies. They will guide you to write an ATS-clearing resume, build a strong online personal brand, and optimize your LinkedIn profile.

Read our reviews to get inspired and join the IK revolution. 

FAQs: Python Data Science Interview Questions

Q1. How Do I Prepare for Python Data Science Interview Questions?

While there is no fixed way to prepare for Python data science interview questions, having a good grasp of the basics can never go wrong. Some important topics you should keep in mind for Python interview questions for data science are: basic control flow for loops, while loops, if-else-elif statements, different data types and data structures of Python, Pandas and its various functions, and how to use list comprehension and dictionary comprehension.  

Q2. Will Python be Allowed in Coding Interviews?

While the simple answer is yes, it can vary from company to company. Python can be allowed in coding rounds, and several companies even use platforms such as HackerRank to conduct Python data science interview questions.

Q3. Explain Arrays in Python Data Science Interview Questions.

Arrays are a data structure, just like lists. With a number of objects of different data types, Python arrays can be repeated and have several built-in functions to handle them. Such conceptual questions play a vital role in Python data science interview questions. So keep this in mind when preparing.

Q4. Which Resources to Use to Prepare for Python Data Science Interview Questions?

Some free resources to prepare for Python data science interview questions are CodeAcademy, FreeCodeCamp, DataCamp, Udacity, and Geeks for Geeks.

Q5. How Long Does it Take to Learn Python?

Typically, it takes around two to six months to learn the fundamentals of Python. But while you can understand the language — the basics at least — in a few minutes, it can take months or even years to master the programming language completely. However, preparing for Python data science interview questions doesn’t take too long.

Related reads:

Author
Dipen Dadhaniya
Engineering Manager at Interview Kickstart
The fast well prepared banner

If you’re looking to build a career in data science, you already know how important Python will be. The significance of Python data science interview questions at interviews has risen exponentially. After all, it is the most widely used language in data science.

When preparing for a data science Python interview, you’ll need to cover all of the major Python concepts so that you’re fully prepared to answer any Python data science interview questions that come your way.

In this article, we cover the commonly asked Python data interview questions. We also give some sample questions that you might be asked during the interview.

Python Data Science Interview Questions and Answers

As you prepare for the Python data science interview questions, keep the following in mind and prepare accordingly. According to our observations, these questions have helped software engineers nail their tech interviews:

Q1. What is Python, and What is it Used for?

An interpreted high-level, general-purpose programming language, Python is often used in building websites and software applications. Apart from this, it is also useful in automating tasks and conducting data analysis. While the programming language can create an array of programs, it hasn’t been designed keeping in mind a specific problem(s).

Q2. List the Important Features of Python.

Some significant features of Python are:

  • It supports structured and functional programmings
  • It developed high-level dynamic data types
  • It can be compiled to byte-code for creating larger applications
  • It uses automated garbage collection
  • It can be used along with Java, COBRA, C, C++, ActiveX, and COM

Q3. What are the Different Built-In Data Types in Python?

Python uses many built-in data types.

Q4. Explain How Python Data Analysis Libraries are Used and List Some Common Ones.

The collection of data analysis libraries used in Python includes a host of functions, tools, and methods that manage and analyze data. Some of the most popular Python data analysis libraries are:

Q5. What is a Negative Index Used for in Python?

You can answer this Python data science interview question by stating that the negative indexes in Python are used to assess and index lists and arrays from the end, counting backwards. For instance, n-1 shows the last time in a list while n-2 shows the second to last.

Q6. What Does it Mean When We Say that Python is an Object-Oriented Language?

When we say Python is an object-oriented language, we mean that it can enclose codes within the objects. When the property permits the storage of the data and the method in a single unit, it is known as the object.

Q7. Explain a Python Module. What Makes it Different from Libraries?

A single file or many files containing functions, definitions, and variables created to perform certain tasks is called a module. It’s a .py extension file that can be imported at any given point and needs to be imported just once.

A library is a collection of reusable functionality of code that’ll allow users to carry out a number of tasks without having to write the code. A Python library doesn’t have any specific use but refers to a collection of modules.

This question is one of the most popular Python data science interview questions.

Q8. What is PEP8?

You can answer this Python data science interview question by stating that coding convection PEP8 contains coding guidelines. These are a set of recommendations put together for the Python language that make the language more readable and easy to use for users.

Q9. Name Some Mutable and Immutable Objects

The ability of a data structure to change the portion of the data structure without needing to recreate it is called mutability. At the same time, immutability is the state of the data structure that can’t be tampered with after its creation.

Q10. What are Generators and Decorators?

You can answer this Python data science interview question by stating that the generator function is responsible for simplifying the process of creating an iterator. A decorator manipulates pre-existing functions or their output, which it does by adding, deleting, or altering characteristics. 

Q11. Differentiate Between %, /, and //?

You can answer this Python data science interview question by describing the following differences:

Q12. What is the Lambda Function?

The following are some of the key Lambda functions:

  • Lambda functions are anonymous as they aren’t declared in the standard manner using the def keyword. Further, it doesn’t even need the return keyword. Both are implicit in the function.
  • These functions have their local namespace and don’t have any access to variables other than those in their perimeter list and those in the global namespace.
  • Examples: x = lambda i,j: i+j

print (x(7,8))

Output: 15

Yet another important question in this list of Python data science interview questions. So prepare accordingly.

Q13. Explain the Map, Reduce and Filter Functions.

The following table can help you learn &  answer this Python data science interview question:

Q14. What is the Difference Between Range, Xrange, and Arange?

The difference between range(), xrange() and arange() is as follows:

Q15. How do you Differentiate Between Global and Local Variables?

You can answer this Python data science interview question by describing the following differences:

Sample Python Data Science Interview Questions for Practice

As you dig deeper and prepare for Python data science interview questions, do practice the following questions as well:

16. Differentiate between lists and tuples in Python.

17. What are positive and negative indices?

18. Define Pass statement in Python.

19. What are the limitations of Python?

20. Give an example of runtime errors in Python.

21. What is meant by compound data types and data structures?

22. Explain with an example what list and dictionary comprehension are.

23. Define tuple unpacking. Why is it important?

24. Differentiate between is and ‘==’

25. How do you differentiate between indexing and slicing?

26. Explain zip() and enumerate() function.

27. What is a default value?

28. What’s the role of namespaces in Python?

29. What is Regex? List some of the important Regex functions in Python.

30. Differentiate between pass, continue and break.

Master Python Interview with Interview Kickstart

Python is one of the most widely used programming languages in the world. It is used in several applications such as machine learning, data science, and more. Interview Kickstart is a leading name in helping people chase and achieve their dreams of getting into tech jobs.

Its Machine Learning course will teach you about mathematical and machine learning concepts, and prepare you for system design and data structure & algorithm-based interviews.

The data science course will prepare you to master data science concepts like data wrangling, data analysis, big data analysis, data visualization, and more. 

These courses, at Interview Kickstart, are taught by instructors with experience of working in FAANG+ companies. They will guide you to write an ATS-clearing resume, build a strong online personal brand, and optimize your LinkedIn profile.

Read our reviews to get inspired and join the IK revolution. 

FAQs: Python Data Science Interview Questions

Q1. How Do I Prepare for Python Data Science Interview Questions?

While there is no fixed way to prepare for Python data science interview questions, having a good grasp of the basics can never go wrong. Some important topics you should keep in mind for Python interview questions for data science are: basic control flow for loops, while loops, if-else-elif statements, different data types and data structures of Python, Pandas and its various functions, and how to use list comprehension and dictionary comprehension.  

Q2. Will Python be Allowed in Coding Interviews?

While the simple answer is yes, it can vary from company to company. Python can be allowed in coding rounds, and several companies even use platforms such as HackerRank to conduct Python data science interview questions.

Q3. Explain Arrays in Python Data Science Interview Questions.

Arrays are a data structure, just like lists. With a number of objects of different data types, Python arrays can be repeated and have several built-in functions to handle them. Such conceptual questions play a vital role in Python data science interview questions. So keep this in mind when preparing.

Q4. Which Resources to Use to Prepare for Python Data Science Interview Questions?

Some free resources to prepare for Python data science interview questions are CodeAcademy, FreeCodeCamp, DataCamp, Udacity, and Geeks for Geeks.

Q5. How Long Does it Take to Learn Python?

Typically, it takes around two to six months to learn the fundamentals of Python. But while you can understand the language — the basics at least — in a few minutes, it can take months or even years to master the programming language completely. However, preparing for Python data science interview questions doesn’t take too long.

Related reads:

Recession-proof your Career

Recession-proof your Data Science Career

Attend our free webinar to amp up your career and get the salary you deserve.

Ryan-image
Hosted By
Ryan Valles
Founder, Interview Kickstart
blue tick
Accelerate your Interview prep with Tier-1 tech instructors
blue tick
360° courses that have helped 14,000+ tech professionals
blue tick
57% average salary hike received by alums in 2022
blue tick
100% money-back guarantee*
Register for Webinar

Recession-proof your Career

Recession-proof your Data Science Career

Attend our free webinar to amp up your career and get the salary you deserve.

Ryan-image
Hosted By
Ryan Valles
Founder, Interview Kickstart
blue tick
Accelerate your Interview prep with Tier-1 tech instructors
blue tick
360° courses that have helped 14,000+ tech professionals
blue tick
57% average salary hike received by alums in 2022
blue tick
100% money-back guarantee*
Register for Webinar

Attend our Free Webinar on How to Nail Your Next Technical Interview

Register for our webinar

How to Nail your next Technical Interview

1
Enter details
2
Select webinar slot
First Name Required*
Last Name Required*
By sharing your contact details, you agree to our privacy policy.
Step 1
Step 2
Congratulations!
You have registered for our webinar
check-mark
Oops! Something went wrong while submitting the form.
1
Enter details
2
Select webinar slot
Step 1
Step 2
check-mark
Confirmed
You are scheduled with Interview Kickstart.
Redirecting...
Oops! Something went wrong while submitting the form.
All Blog Posts
entroll-image
closeAbout usWhy usInstructorsReviewsCostFAQContactBlogRegister for Webinar