This examination evaluates a student’s conceptual understanding and programming ability in Python, covering core syntax, functions, file handling, data visualization, loops, strings, lists, numerical computing, and problem-solving skills.
The paper is divided into three sections, progressively testing basic concepts, applied programming, and advanced logic-building.
SECTION A – Short Answer Questions (14 Marks)
7 questions × 2 marks
This section checks essential, fundamental Python concepts that form the base for programming and data processing.
Topics Covered:
1. List Comprehension
Understanding how lists are created in a single line using expressions and iteration.
2. Difference Between / and // Operators
Floating-point division vs floor division with examples.
3. Output Prediction
Given a function involving .split() and join(), students predict final output.
4. Using Functions From Another File (module import)
How main.py accesses functions defined in library.py using import, from ... import, and module references.
5. Difference Between linspace and arange
Numerical range generation in NumPy for plotting and mathematical applications.
6. Error Identification in List/String Operations
Mutability vs immutability: why modifying a string index fails.
7. Functions of Matplotlib & Pandas
Basic plotting commands, data structures, and operations.
This section judges clarity of Python fundamentals and error understanding.
SECTION B – Applied Python Programming (21 Marks)
Attempt any 3 questions – each 7 marks
This section requires writing Python programs, demonstrating logic, and implementing operations on data structures, files, and functions.
Questions Cover:
1. Unpacking Tuples, Mutable Sequences & String Concatenation
Explaining with code how tuple unpacking works, modifying elements in lists, and joining strings.
2. List Slicing Operations
Performing multiple slicing tasks on a list, such as:
• reverse slices
• mid-segment extraction
• even-index elements
• reversing part of a list
• dividing and replacing elements
3. Perfect Square Function
Implementing perfect_square(number) that returns the number only if a perfect square; otherwise returns −1.
4. File Handling – Reverse Characters With Commas
Reading a file and rewriting content as comma-separated characters:
Example: "Hello!!" → "H,e,l,l,o,!,!"
5. Plotting Dataset Using Matplotlib
Constructing bar/line plots for calories, potassium, and fat from given food dataset.
This section evaluates programming fluency, slicing, iteration, logic writing, and basic data visualization.
SECTION C – Logical & Real-World Python Applications (35 Marks)
Each section contains two options; students attempt ONE.
3. String Manipulation & Sorting (7 Marks)
Option A – removenth(s, n)
Function to remove the nth character from a string, handling edge cases when n ≥ len(s).
Option B – Sorting comma-separated words
Program to accept input like:
without, hello, bag, world
Sort alphabetically and print result.
4. Password Validation or Loop Demonstrations (7 Marks)
Option A – Password Validator
Program enforcing:
✓ lowercase letter
✓ uppercase letter
✓ digit
✓ special char ($#@)
✓ length 6–12
Valid passwords printed comma-separated.
Option B – Demonstrate While & For Loops
Explanation with practical examples on iteration, termination, nested loops, and range usage.
5. Nested Lists & Text Filtering (7 Marks)
Option A – Smallest List Finder
Function ret_smaller(l) returning list with smallest length; ties resolved by first occurrence.
Option B – Text Filters
Filtering rules:
extract numbers
extract strings starting with vowels
extract strings containing nouns (Agra, Ramesh, Tomato, Patna)
Used to clean messy text through Python list comprehensions and filters.
6. File Processing & Digit-only Words (7 Marks)
Option A – Convert Numbers to Words in File
Program reads text and replaces numeric digits with word equivalents inside the file.
Option B – Extract Digit-only Words
Program reading a file and printing only those words composed purely of digits.
7. CSV Processing & Calculator App (7 Marks)
Option A – Process cities.csv
Tasks:
• read CSV
• remove last column → store in one array
• store last column separately
• plot first two columns using matplotlib
Option B – Build a Simple Calculator
Buttons/functions:
addition
– subtraction
× multiplication
÷ division
C clear
Python implementation using functions or GUI (Tkinter).
Purpose of This Examination
This exam ensures that students can:
Use Python for solving computational problems
Implement functions, loops, slicing, and data structures
Perform file handling, string manipulation, and data cleaning
Visualize data using matplotlib
Work with CSV files and external modules
Understand program errors and fix them
Apply logic to real-world tasks like password validation and text filtering
Build structured, reusable Python programs
This paper strengthens student ability to think algorithmically and apply Python in practical domains including data science, automation, and application development.
