If you\u2019re preparing for a data science interview, Python will be one of the core areas you\u2019ll be tested on. Companies usually check your understanding of Python basics, data handling with NumPy and Pandas, data visualization concepts, and how you apply Python thinking to real-world problems. You can prepare effectively by revising common interview questions, practicing small exercises, and exploring real examples.<\/p>\n\n\n\n
Basic Python Data Science Interview Questions<\/h2>\n\n\n\n
The basic level covers Python topics such as data types, object-oriented programming<\/a>, memory management, data manipulation, and analysis. Let\u2019s look into the questions.<\/p>\n\n\n\n Python offers several built-in data types that are foundational for data manipulation and programming. These include:<\/p>\n\n\n\n Understanding these data types is crucial as they form the basis of Python programming, especially in data science<\/a>, where data manipulation and analysis are key.<\/p>\n\n\n\n Python is renowned for its robust libraries that simplify data analysis, including:<\/p>\n\n\n\n These libraries are integral for performing complex data analysis tasks efficiently in Python<\/a>.<\/p>\n\n\n\n Negative indexing in Python allows access to the list elements from the end. For instance, consider the list This feature is particularly useful for quickly accessing data from the end without needing to know the length of the list.<\/p>\n\n\n\n Dictionary comprehension offers a concise way to create dictionaries. The syntax is This creates a dictionary Yes, Python supports object-oriented programming (OOP) principles, making it a multi-paradigm language that facilitates OOP with classes and objects. It allows for concepts like inheritance, encapsulation, and polymorphism, which are fundamental in creating reusable and modular code.<\/p>\n\n\n\n Choosing between Seaborn and Matplotlib<\/a> depends on the specific needs:<\/p>\n\n\n\n For detailed customization, Matplotlib is ideal, while for high-level statistical plotting, Seaborn is more convenient.<\/p>\n\n\n\n The primary difference is mutability:<\/p>\n\n\n\n This distinction affects performance and usage: tuples can be faster and are useful where fixed data is needed.<\/p>\n\n\n\n Dictionaries can be sorted by keys or values<\/a> using This results in dictionaries sorted by keys and values, respectively.<\/p>\n\n\n\n Understanding these structures is fundamental for effective data manipulation in Pandas.<\/p>\n\n\n\n Memory de-allocation in Python is generally handled by Python’s garbage collector, which deallocates memory not in use automatically. However, in cases of circular references or references from global namespaces, memory might not be freed upon Python exit, depending on the environment and operating system.<\/p>\n\n\n\n If you are interested in getting started with Data Science and love to learn by reading, you can use HCL Guvi\u2019s FREE E-book on <\/em>Master the Art of Data Science – A Complete Guide<\/em><\/a>. This e-book is an overall roadmap and explains in detail about each step towards a career in data science.<\/em><\/p>\n\n\n\n The intermediate level covers topics such as built-in functions, errors, data structures like stack, queue, and string manipulation. Let\u2019s dive into the questions.<\/p>\n\n\n\n A key error in Python occurs when you try to access a key element, but there is no match in the actual dictionary. Python throws KeyError only after iterating through the dictionary to look for the key. For example, a student dictionary is mapped with their role numbers between 1 to 10 and their names. When you try to access a student with a roll number 11, Python will throw a KeyError since the roll numbers are mapped till 10.<\/p>\n\n\n\n To solve this error, you can use the get() method to check for a key; if there is no matching key, it will return a null value. The most efficient way is to use a try and catch block, if there is no matching, then it will execute the catch block.<\/p>\n\n\n\n This problem can be solved using a built-in method called intersect(). Check out the code below<\/p>\n\n\n\n1. What built-in data types are used in Python?<\/h3>\n\n\n\n
\n
2. How are data analysis libraries used in Python? What are some of the most common libraries?<\/h3>\n\n\n\n
\n
![\"python](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2024\/08\/1-1.png\" "\\"\\"")
<\/figure>\n\n\n\n3. What is negative Indexing in Python? [with example]<\/h3>\n\n\n\n
a = [1, 2, 3, 4, 5]<\/code>:<\/p>\n\n\n\n\n
a[-1]<\/code> would give the last element, which is 5<\/code>.<\/li>\n\n\n\na[-2]<\/code> would return 4<\/code> the second last element.<\/li>\n<\/ul>\n\n\n\n4. What is dictionary comprehension in Python? [with example]<\/h3>\n\n\n\n
{key: value for vars in iterable}<\/code>. For example:<\/p>\n\n\n\nsquares = {x: x*x for x in range(6)}<\/code><\/pre>\n\n\n\nsquares<\/code> where each key is an integer and its value is the square of the key.<\/p>\n\n\n\n5. Is Python an object-oriented programming language?<\/h3>\n\n\n\n
![\"object-oriented](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2024\/08\/2-1.png\" "\\"\\"")
<\/figure>\n\n\n\n6. What library would you prefer for plotting Seaborn or Matplotlib?<\/h3>\n\n\n\n
\n
7. What is the difference between lists and tuples in Python?<\/h3>\n\n\n\n
\n
![\"Tuples](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2024\/08\/3-1.png\" "\\"\\"")
<\/figure>\n\n\n\n8. How would you sort a dictionary in Python?<\/h3>\n\n\n\n
sorted()<\/code>:<\/p>\n\n\n\nmy_dict = {'one': 1, 'three': 3, 'five': 5}\nsorted_by_key = {k: my_dict[k] for k in sorted(my_dict)}\nsorted_by_value = {k: v for k, v in sorted(my_dict.items(), key=lambda item: item[1])}<\/code><\/pre>\n\n\n\n9. What is the difference between a series and a data frame in Pandas?<\/h3>\n\n\n\n
\n
10. Is memory de-allocated when you exit Python?<\/h3>\n\n\n\n
Intermediate Python Data Science Interview Questions<\/h2>\n\n\n\n
11. What is a keyError in python?<\/h3>\n\n\n\n
12. Given two arrays, write a Python function to return the intersection of the two. For example, X = [1,5,9,0] and Y = [3,0,2,9] it should return [9,0]<\/h3>\n\n\n\n
![\"How](\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2024\/08\/4-1.png\" "\\"\\"")
<\/figure>\n\n\n\n