This study utilizes Python for analyzing the spread pattern of COVID-19 during a pandemic. Its purpose is to identify the dynamics and influencing factors of COVID-19 spread, as well as to explore Python's data visualization capabilities for presenting clear and understandable information. The research relies on open data from governmental or related institutions. The analysis includes identifying the ten countries with the highest case counts and determining each continent's contribution to COVID-19 cases. Various visualizations like bar charts, pie charts, and maps are employed to facilitate better comprehension and decision-making. The study's findings demonstrate the effectiveness of Python in analyzing COVID-19 spread patterns, offering valuable insights for addressing the challenges associated with the pandemic. Moreover, Python proves to be a highly effective tool for visualizing data, aiding in understanding the spread patterns of COVID-19. Overall, this research showcases the relevance and usefulness of Python in both analyzing and visualizing COVID-19 data, which can greatly contribute to efforts aimed at controlling and managing the pandemic.