We covered geocoding and geospatial analysis in today’s lecture, which introduced the robust Python package GeoPy. Using the construction of several plot kinds, including Geohist, the professor demonstrated how to map and visualize data points on a map of the United States using GeoPy. The students used GeoPy to determine the locations of police shootings, demonstrating the practical application of geospatial data analysis in real-world scenarios. That application even extended to California.
Additionally, a density-based clustering method called DBSCAN was presented. There are four unique clusters within the dataset, as the professor demonstrated while integrating GeoPy with DBSCAN to find clusters. When it comes to locating hidden spatial patterns in data, this method can be quite helpful.
In addition, the class had an interesting conversation regarding the connection between crime rates and police shootings. We investigated the fascinating idea that, even in places with lower total crime rates, crime intensity might play a significant role. This raised a number of issues and suggested possible lines of inquiry for additional research.
In conclusion, the course today covered a thorough overview of geospatial analysis with GeoPy, presented a useful clustering technique in DBSCAN, and started a stimulating investigation into the relationships between crime and police shootings