Class Performance Analyzer Using Python
Overview This project is a Python program that analyzes the academic performance of a class using basic programming logic. The program calculates the class average, identifies students who are performing below a defined threshold, and evaluates whether the overall class performance is acceptable.
The project focuses on practicing Python fundamentals such as loops, lists, conditional statements, and basic statistical calculations.
Technologies Used Python
Dataset The program contains two lists
Student names Student marks
Example data used in the program
Names Aman Riya Rahul Sneha Karan
Marks 45 38 72 88 55
Program Features Calculates the overall class average Determines a performance threshold based on the class average Identifies students whose marks fall below the threshold Displays the names and marks of students at academic risk Separates marks into above threshold and below threshold groups Evaluates the overall class performance
Performance Logic
The program first calculates the class average. A performance threshold is defined as ten marks below the class average. Students scoring below this threshold are considered at risk. The program also checks whether the number of below threshold students indicates poor class performance.
Program Workflow
Student names and marks are stored in lists The program calculates the total marks and class average A threshold value is created using the class average Students scoring below the threshold are identified Their names and marks are printed as at risk students The program counts students performing below the threshold Finally the program evaluates whether the class performance is acceptable
Learning Outcome
This project helps strengthen understanding of
Loop based data processing List indexing and list operations Basic statistical calculations Simple performance analysis logic
These types of operations are commonly used in early stage data analysis tasks.
Author
Uday Bhaskar Aspiring Data Science learner focusing on Python and data analysis.