The Solution

In the Withdrawal Form Automation Script project, I used Pandas and Numpy to automate the processing and analysis of over 2,000 student withdrawal forms, saving 20 hours of manual work. Pandas were used in handling the Excel data, allowing for efficient manipulation, filtering, and categorization of withdrawal reasons. I used Numpy to optimize numerical operations, enabling me to handle large datasets with improved performance. The script analyzes the text data by identifying keywords related to medical, mental health, financial, academic, registration errors, and other categories. Using pandas, I generated categorized outputs that were written back into a new Excel file for better management and visualization. This not only enhanced administrative efficiency but also provided valuable insights into student demographics, leading to more informed decision-making by management. This solution was designed for ease of usage and quickness of implementation, as this was one of the busiest times during our office.