AUTOMATED RESULT ANALYSIS USING PYTHON AND STREAMLIT
Paras Deshpande, Lokesh Keerthi, Nayan Katiyara, Kartikeya Mane, Vandana Dixit · International Journal of Data Science and Analytics · 2025
Educational institutions worldwide continuously generate large volumes of student performance data, which necessitate efficient processing, detailed analysis, and meaningful interpretation .Traditionally, result analysis has involved manual handling of data, spreadsheet computations, and basic statistical methods.These conventional techniques are time-consuming, error-prone, and lack the interactive and dynamic visualization features needed for modern educational environments With advancements in data science, programming languages, and web-based frameworks, there is a growing opportunity to develop sophisticated automated result analysis systems that can transform educational data processing .This research introduces an innovative automated system designed to streamline the complete process of academic result analysis.The system employs technologies such as the Python Imaging Library (PIL) for converting PDF files into images, and Tesseract OCR for accurate text extraction and localization using bounding boxes.The extracted text is structured and appended into a CSV file, serving as the primary dataset for further analysis.