Python interview questions for data engineer

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In this blog let’s discuss some of the Python interview questions for a data engineer role. This blog contains 10 questions and answers to practice and crack your next interview

1) What is the difference between a list and a tuple in Python?

Lists are mutable, meaning their elements can be changed after creation, while tuples are immutable, meaning their elements cannot be changed after creation

2) Explain the purpose of the “Pandas” library in Python.

Pandas is a powerful data manipulation library in Python. It provides data structures like DataFrame for efficient data manipulation and analysis. It is widely used in data engineering for cleaning, transforming, and analyzing data.

3) How can you handle missing or null values in a DataFrame using Pandas?

Pandas provides methods like dropna() to remove missing values and fillna() to fill or impute missing values with a specified value or a calculated value like mean or median.

4) What is the purpose of virtual environments in Python?

Virtual environments are used to create isolated Python environments for projects. They help manage dependencies and avoid conflicts between different projects by keeping their dependencies separate.

5) Explain the difference between SQL and NoSQL databases.

SQL databases are relational and use structured query language for defining and manipulating data. NoSQL databases are non-relational and provide a more flexible data model, often using documents, key-value pairs, or graphs.

6) How do you read a CSV file into a Pandas DataFrame?

You can use the pd.read_csv('filename.csv') function from the Pandas library to read a CSV file into a DataFrame.

7) What is the Global Interpreter Lock (GIL) in Python?

The Global Interpreter Lock is a mechanism in Python that allows only one thread to execute Python bytecode at a time in a single process. It can impact the performance of multithreaded Python programs.

8) How can you handle large datasets that do not fit into memory in Pandas?

Pandas provides the chunksize parameter in the pd.read_csv() function to read large datasets in smaller chunks. Additionally, you can use tools like Dask or Vaex for handling larger-than-memory datasets.

9) What is the purpose of the __init__ method in Python classes?

The __init__ method is a special method in Python classes that is automatically called when an object is created. It is used to initialize the attributes of the object.

10) Explain the concept of map-reduce in the context of big data processing.

Map-reduce is a programming model used for processing and generating large datasets in parallel across a distributed cluster. The “map” step processes and filters data, and the “reduce” step aggregates and summarizes the results. Hadoop is a popular framework for implementing map-reduce.

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