Python Programming Laboratory Notes
Subject Overview
The practical companion to Python Programming, building programs around primality testing, string manipulation, NumPy array operations, dictionary-based letter frequency counting, tuple operations, alternate-line file copying, exception handling, and plotting sine/
Subject at a glance
1
Units
14
Topics
2
Credits
1
Infographics
Unit-wise Syllabus
1 units — open any unit for detailed topic-wise notes, diagrams and important exam questions
- Prime number check
- power calculation
- even/odd parameterized function
- alternating series summation
- menu-driven string operations (character frequency, replace, remove occurrences)
- string search returning indices
- NumPy array operations (fill, min/max, dot product, reshape)
- letter-frequency dictionary
- tuple operations (split, filter evens, concatenate, min/max)
- alternate-line file copying
- ZeroDivisionError handling
- duplicate-detection exception
- sine/cosine/polynomial/exponential curve plotting
- monthly profit line plot
Logic
Prime check, series sums, even/odd
Strings
Frequency, replace, search
NumPy
Fill, min/max, dot product, reshape
Files and errors
Copying files, ZeroDivisionError
Plots
Sine/cosine curves, profit line plot
Study guide
The lab covers programming and data handling exercises: prime check, power calculation, an even or odd function, alternating series summation, menu-driven string operations, string search returning indices, NumPy array operations (fill, min and max, dot product, reshape), a letter-frequency dictionary, tuple operations, alternate-line file copying, ZeroDivisionError handling, a duplicate-detection exception, plotting sine, cosine, polynomial and exponential curves and a monthly profit line plot. Run each program with normal, boundary and invalid inputs.
Why Python Programming Laboratory Matters
These exercises cover the exact Python skills used in data analysis and automation, and they build the confidence needed for coding tests.
How to Prepare for Python Programming Laboratory
- Write programs yourself first and use documentation rather than copying answers.
- Test with invalid inputs to practise exception handling.
- Label every plot with title, axes and legend.
Python Programming Laboratory: Frequently Asked Questions
What is done in the Python lab?
String, list, tuple and dictionary programs, NumPy operations, file handling, exception handling and plotting with graphs.