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Description
| SESSION | APRIL 2025 |
| PROGRAM | BACHELOR OF COMPUTER APPLICATIONS (BCA) |
| SEMESTER | 5 |
| COURSE CODE & NAME | DCA3104 PYTHON PROGRAMMING |
SET-I
Q1. a) Explain mutable and immutable datatypes of python.
- b) How do membership and identity operators work? Explain with example 5+5
Ans 1.
Understanding Data Types in Python
In Python, every value has a data type, and based on the ability to change the value without altering the object’s identity, data types are classified into mutable and immutable. Understanding this distinction is essential for proper memory management and behavior prediction of variables during program execution.
Mutable Data Types
A mutable data type allows changes to its content after the object has been created. This means we can modify,
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Q2. a) How instance variables are different from class variables?
- b) Explain the use of following string functions: – upper(), lower(), isdigit(), isalpha(), split(), join() with example. 5+5
Ans 2.
- a) How Instance Variables Are Different from Class Variables
Understanding Instance Variables
Instance variables are variables that are defined within a class but are specific to each object or instance of that class. They are created inside a constructor or any instance method using the self keyword and hold data that is unique for each instance.
For example:
class Student:
def __init
Q3. a) What is list? Explain insert() and append() methods with example.
- b) How to create private and protected variables in class? Explain its importance. 5+5
Ans 3.
- Definition of List in Python
A list in Python is an ordered, mutable, and heterogeneous collection that can hold a variety of object types, such as integers, strings, and even other lists. Lists are defined using square brackets.
Example:
my_list = [1, 2, 3, ‘Python’]
Python lists are dynamic and support operations such as addition, deletion, indexing, slicing, and iteration.
Append
SET-II
Q4. a) How do variable length and keyword arguments works? Explain with program.
- b) Explain differences between remove(), discard( ) and pop( ) method for deleting elements from set. 5+5
Ans 4.
- Understanding Variable-Length Arguments
In Python, functions can be defined to accept a variable number of arguments using *args for non-keyworded and **kwargs for keyworded arguments. These are useful when the number of inputs is unknown during function definition.
The *args syntax is used to send a variable number of non-keyword arguments to a function. Internally, it converts the arguments into a tuple. For example:
def add_
Q5. What is an exception handling? How do you handle multiple exceptions in python? Explain with example. 10
Ans 5.
Understanding Exception Handling in Python
Exception handling in Python is a mechanism to gracefully manage run-time errors. These errors, known as exceptions, occur during execution and can interrupt the flow of a program. Python provides the try-except block to handle such errors and continue program execution instead of crashing.
The try block contains code that might raise an exception. If an error occurs, it is caught by the except block
Q6. a) How to handle missing data using pandas? Explain dropna() and fillna() methods.
- b) What are DDL and DML commands? Explain. 5+5
Ans 6.
- Handling Missing Data in Pandas
In real-world data analysis, datasets often contain missing values. Pandas offers efficient tools to handle such data using methods like dropna() and fillna(). These methods allow either removing or imputing missing entries to maintain data integrity.
dropna() Method
The