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NumPy Interview Questions & Answers 2025 | NumPy Interview Questions for Freshers & Experienced 🔥Professional Certificate Program in AI and Data Science: https://www.upgrad.com/bootcamps/job-... 🔥Liverpool John Moore University MS In Data Science: https://www.upgrad.com/data-science-m... 🔥IIIT Bangalore Post Graduate Program in Data Science & AI: https://www.upgrad.com/data-science-p... 🔥Graduate Certificate Program in Data Science & AI: https://www.upgrad.com/graduate-certi... NumPy (Numerical Python) is a library for working with arrays and mathematical operations in Python. Here are some importance of NumPy and common interview questions: Importance of NumPy Interview Questions 1. Assesses Problem-Solving Skills NumPy questions evaluate a candidate's ability to solve numerical problems, think critically, and apply mathematical concepts to real-world scenarios. 2. Evaluates Programming Skills NumPy is a Python library, so questions about it also assess a candidate's Python programming skills, including syntax, data structures, and control structures. 3. Relevance to Data Science and Scientific Computing NumPy is a fundamental library in data science and scientific computing. Questions about NumPy demonstrate a candidate's ability to work with numerical data, perform statistical analysis, and visualize results. 4. Indicates Familiarity with Scientific Computing NumPy is widely used in scientific computing, so questions about it indicate a candidate's familiarity with this field and their ability to work with large datasets, perform simulations, and analyze results. 5. Assesses Ability to Optimize Code NumPy questions often involve optimizing code for performance, which is critical in scientific computing and data science. Candidates who can optimize NumPy code demonstrate their ability to write efficient, scalable code. 6. Evaluates Understanding of Mathematical Concepts NumPy questions require a strong understanding of mathematical concepts, such as linear algebra, calculus, and statistics. Candidates who can answer NumPy questions demonstrate their grasp of these concepts and their ability to apply them to real-world problems. 7. Indicates Ability to Work with Multi-Dimensional Data NumPy is designed to work with multi-dimensional arrays, so questions about it assess a candidate's ability to work with complex data structures and perform operations on them. 8. Relevance to Machine Learning and Deep Learning NumPy is used extensively in machine learning and deep learning, so questions about it demonstrate a candidate's ability to work with these technologies and build predictive models. 9. Assesses Ability to Debug Code NumPy questions often involve debugging code, which is an essential skill in software development. Candidates who can debug NumPy code demonstrate their ability to identify and fix errors. 10. Evaluates Ability to Communicate Technical Ideas Finally, NumPy questions assess a candidate's ability to communicate technical ideas clearly and effectively. Candidates who can explain complex NumPy concepts demonstrate their ability to communicate with technical and non-technical stakeholders. NumPy Interview Questions: 00:52 - 1. What is NumPy? 01:39 - 2. What are the uses of NumPy? 02:25 - 3. Why is NumPy Preferred to other programming tools such as IDL, MATLAB, Octave or Yorick? 03:04 - 4. what are the various features of NumPy? 04:14 - 5. How can you install NumPy on windows? 04:53 - 6. List the advantages NumPy Arrays have over (nested) Python lists? 05:58 - 7. List the steps to create a 1D array and 2D array 06:47 - 8. How do you create a 3D array? 07:28 - 9. What are the steps to use shape for a 1D array, 2D array and 3D/ND array respectively? 08:46 - 10. How can you identify the datatype of a given NumPy array? 10:14 - 11. What is the procedure to count the number of times a given value appears in an array of integers? 10:35 - 12. How do you check for an empty (zero Element) array? 11:47 - 13. What is the procedure to find the indices of an array in NumPy where some condition is true? 12:44 - 14. Shown below is the input NumPy array. Delete column two and replace it with the new column given below. 14:57 - 15. Create a two 2-D array. Plot it using matplotlib