Student Record Analysis Using NumPy for Efficient Data Processing and Insights
Analyzed student data using the NumPy library in Python to calculate averages, find top scores, and identify performance trends efficiently.
This Python program performs automated analysis of student performance using structured data on student marks. It leverages NumPy for numerical operations and includes features such as tabular display, result classification, and statistical insights like average, standard deviation, and variance.