Python is the most demanded language in the programming domain. In this python basic interview questions blog, I will introduce you to the most frequently asked questions in the interviews, which will help you with different expertise levels to reap the maximum benefit from this blog.

I am sharing these interview questions so that you all can revise your basic concepts and gain knowledge from this blog before sitting in an interview. As you are a beginner, the interviewer will certainly check your understanding of Python Fundamentals and how much knowledge you have. So, let’s start exploring the basic python interview questions and answers –

The most frequently asked question for freshers in python interview is:

  1. What is the difference between LISTS & TUPLES?

The major difference between tuples and lists is that a list can be changed, whereas a tuple cannot. This means that lists are mutable, but a tuple is immutable. Lists are slower than tuples.

  1. Why Python is an interpreted language. Can you explain with reason?

Python is an interpreted object-oriented programming (OOPSlanguage i.e. each time you write Python programs, the interpreter checks through the code for errors and then interprets the instructions into machine-readable bytecode/ Machine language

  1. Python programming language is case sensitive or not?

Yes, Python language is a case sensitive language. Or we can say, it cares about lowercase or uppercase. For example, it distinguishes between “Machine” & “machine”.

  1. What are the 4 data types in Python?

Following are the built-in data type of Python:

Numeric (integer, float)

Sequence Type (strings, lists, tuples)

Boolean

Set

Dictionary

  1. What is set () in Python?

The set() function creates a set object. The items in a set list are unordered and unindexed so it will appear in random order and used to store multiple items in a single variable. Set is one of 4 built-in data types in Python used to store collections of data.

  1. What is slicing? 
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In Python, slicing is a feature that enables accessing parts of sequences like lists, tuples, and strings. You can also use slicing to delete or modify the items of mutable sequences such as lists.

  1. What is indexing in python?

“Indexing” means referring to an element of an iterable by its position within the iterable.

  1. How does Python indexing work?

Python follows zero-based indexing. It means that the first element has an index 0, the second has index 1, and so on.

For example,

Language= (“python”, ”R”, ”SQL”, ”Ruby”)

Here, “python” has an index 0

“R” has an index 1.

“SQL” has an index 2.

“Ruby” has an index 3.

  1. What is a negative index in Python? 

Python arrays and list items can be accessed with positive or negative index. 

For a positive index, 0 is the first index, 1 is the second index and so on. For negative index, (-1) is the last index and (-2) 

is the second last index and so on.

  1. What is the Len () function in Python?

Len () is a built-in function in python. We use the Len () to get the length of the given string, array, list, tuple, dictionary, etc.

 For example, Len (“Python”) will return 6 because there are 6 characters in “Python”.

  1. What are Python Libraries?

Python libraries are a collection of Python packages.

Datetime, time and OS are commonly used standard libraries. These libraries come with every installation of Python, that’s why they are called as standard libraries.

The majorly used libraries for data science with Python are external, which means they do not come standard with Python. 

The external data science libraries we generally use are NumPy, Pandas, Seaborn, matplotlib, scikit learn.

Then the interviewer must ask you can you explain the difference between NumPy and Pandas?

So, here is the answer.

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NumPy is a Python library that offers (arrays) multidimensional data structures on which operations can be performed quicker than standard Python data structures (for example, lists). NumPy is used for performing the various numerical computations and processing of the multidimensional and single-dimensional array elements. The calculations using NumPy arrays are much faster than the normal Python array.

Pandas stores data in 2D tabular structures. In which columns represent different variables and rows correspond to samples. 

The NumPy module mainly works with numerical data whereas, Pandas module works with tabular data.

NumPy module offers a powerful object called Array whereas, the Pandas provides some sets of powerful tools like DataFrame and Series that mainly used for analyzing the data.

  1. What is describe () in Python?

Describe () computes various properties including the mean, 

Standard deviation, percentile, minimum, and maximum for each column of a DataFrame. This table gives an idea of how everything is distributed in a dataset.

2. How do you find the null value in Python?

Missing Data or NaN values is a very big problem in real-life scenarios.

In order to find missing values in Pandas DataFrame, we use a function isnull() & notnull(). Both functions help in checking whether a value is null or not. 

4. Is python open source?

Yes, Python is an open-source, simple, easy to use and learn, readable, and well-structured language which is developed under an OSI-approved open source license, which makes it free to use even for commercial purposes.

Anyone can download Python for free and can write codes in a matter of minutes. Python is easy-to-learn for beginners. 

This brings us to the end of the blog on Python questions for freshers. We hope that you were able to gain some insights from this blog and are now better equipped with the python interview questions and python programming questions. 

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