Developed a Python automation script to streamline the analysis of COVID-19 case and death data across multiple regions, significantly reducing manual entry time and minimizing human error. Engineered a Python tool using openpyxl to apply conditional formatting across extensive Excel datasets, facilitating quick visual analysis of public health data. Created a feature for conditional cell coloring based on comparative data analysis, improving the visualization of data alignment with benchmarks set by authoritative COVID-19 statistics from Johns Hopkins University. The Original code can be found on cosmos uta project https://cosmos.uta.edu/