Geospatial data is important for many contemporary technologies such as Geographic Information Systems (GIS), remote sensing, satellite imagery analysis, and spatial data science. The increasing amounts and complexities of geospatial datasets make it essential for geospatial analysts to have the tools that allow them to process, analyze, manipulate, and visualize spatial data effectively. Python has gained popularity among professionals who have to deal with geospatial datasets because of its advantages in flexibility, libraries, and ability to automate processes.