30 Essential Data Science Interview Questions from Python & SQL One Must Know

Are you preparing for a data science interview? Mastering Python, Pandas, and SQL is critical if you want to stand out. These tools are essential for data analysis, data manipulation, and querying databases, making them a must-have skill set for any data scientist. In this blog, we’ll cover 35 of the most important interview questions on Python, Pandas, and SQL that you need to know. Whether you’re a beginner or brushing up for a high-level role, this guide is for you!

Python Interview Questions for Data Science

1. What is Python? Why is it popular for Data Science?
Python is an interpreted, high-level, general-purpose programming language. It is popular in data science because of its simplicity, ease of use, and vast ecosystem of libraries like Pandas, NumPy, and Scikit-learn, which makes data manipulation, statistical analysis, and machine learning easy.

2. What is a Python list, and how is it different from a tuple?
A list is mutable, meaning you can modify its content (add, remove, update elements), while a tuple is immutable, meaning it cannot be changed once created.

3. What are Python dictionaries?
Dictionaries are ordered collections of data in Python, stored in key-value pairs. They are mutable, meaning their values can be changed.

4. How do you handle exceptions in Python?
Exceptions in Python are handled using the try...except block. Code that may raise an error is placed inside the try block, and the error is caught in the except block.

5. What are lambda functions in Python?
Lambda functions are anonymous, small functions defined using the lambda keyword. They are typically used for single-line functions and passed as arguments to other functions.

6. How does Python handle memory management?
Python uses an automatic memory management system called a garbage collector, which recycles memory when objects are no longer in use.

7. What is the use of the map() function in Python?
The map() function applies a given function to all items in an input list (or iterable) and returns an iterator with the results.

8. What is the __init__ method in Python?
__init__ is a constructor method in Python classes. It is used to initialize objects when a new instance of the class is created.

9. How does list comprehension work in Python?
List comprehension provides a concise way to create lists in Python. It replaces the need for loops to append items to a list. Example: [x**2 for x in range(5)] creates a list of squares from 0 to 4.

10. What is the difference between a while loop and a for loop?
The while loop keeps executing the block of code as long as the given condition is True. It is typically used when the number of iterations is not known in advance and depends on a condition.

The for loop iterates over a sequence (such as a list, tuple, string, or range) or any other iterable object. The number of iterations is fixed based on the length of the sequence or range.

Pandas Interview Questions for Data Science

11. What is Pandas?
Pandas is a powerful open-source data analysis and manipulation library for Python. It provides fast, flexible data structures like DataFrame and Series for managing data efficiently.

12. How do you create a DataFrame in Pandas?
A DataFrame can be created by passing a dictionary, list, or NumPy array to the pd.DataFrame() function. For example:

import pandas as pd 
data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]} 
df = pd.DataFrame(data)

13. How do you handle missing values in a Pandas data frame?
Missing values can be handled using functions like isna() to detect missing values, fillna() to replace missing values, and dropna() to remove rows/columns with missing data.

14. What is the difference between loc and iloc in Pandas?

• loc: Accesses rows/columns by labels.
• iloc: Accesses rows/columns by index positions.

15. How do you concatenate DataFrames in Pandas?
DataFrames can be concatenated using pd.concat() for stacking along a particular axis (rows or columns).

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16. How do you group data in Pandas?
Pandas offers the groupby() function to group data based on one or more columns. You can then apply aggregate functions like sum(), mean(), etc.

17. What is a Pandas Series?
A Pandas Series is a one-dimensional labeled array capable of holding any data type. It’s like a column in a data frame.

18. How do you merge DataFrames in Pandas?
DataFrames can be merged using the merge() function, which behaves similarly to SQL joins (left, right, inner, outer joins).

19. How do you reset the index of a data frame?
Use reset_index() to reset the index of a data frame and drop=True to avoid keeping the old index as a column.

20. How do you filter rows in a data frame?
You can filter rows using conditional statements. For example:

df[df['Age'] > 25]

SQL Interview Questions for Data Science

21. What is SQL?
SQL (Structured Query Language) is used for managing and manipulating relational databases by querying, updating, and modifying the data.

22. What are the different types of SQL joins?

• INNER JOIN: Returns records with matching values in both tables.
• LEFT JOIN: Returns all records from the left table and matches records from the right table.
• RIGHT JOIN: Returns all records from the right table and matches records from the left table.
• FULL JOIN: Returns all records when there is a match in either table.

23. What is a primary key?
A primary key is a unique identifier for a record in a table. It ensures that each record is unique and cannot contain null values.

24. What is the difference between DELETE and TRUNCATE?

• DELETE: Removes rows one by one and can be rolled back.
• TRUNCATE: Deletes all rows in a table instantly and cannot be rolled back.

25. How do you fetch unique records from a table?
You can use the DISTINCT keyword in the SELECT statement to fetch unique records.

26. What are indexes in SQL, and why are they used?
Indexes are used to speed up database queries by providing a quick lookup of data. However, they may slow down data modification operations like insert and update.

27. How do you join three tables in SQL?
You can join three tables by writing consecutive JOIN clauses. Example:

SELECT * FROM Table1 JOIN Table2 ON Table1.id = Table2.id JOIN Table3 ON Table2.id = Table3.id;

28. What is normalization in SQL?
Normalization is the process of organizing a database to reduce redundancy and improve data integrity. It involves dividing a database into smaller, related tables.

29. What is a foreign key?
A foreign key is a field in one table that refers to the primary key of another table. It ensures referential integrity between two tables.

30. What is a subquery?
A subquery is a query nested inside another query. It is used to filter data in the outer query.

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