GIS vector datasets are typically composed of point, line, or polygon features. One of the principles of GIS is that things that are closer together geographically are more related than things that are further apart. When you have a set of related features, often, it's too much detail for the analysis you're trying to accomplish. It can be useful to generalize them to speed up processing or simplify a map. This type of operation is called aggregation. A common example of aggregation is to combine a set of local political boundaries into a larger political boundary such as counties into a state or states into a country or countries into continents.
In this example, we'll do just that. We'll convert a dataset comprising all of the counties in the US state of Mississippi into a single polygon representing the entire state. The Python Shapely...