Often, the data we work with requires preprocessing; sometimes, that includes gathering additional information to add context or transform existing information. Typical examples of that are geocoding and reverse geocoding—the processes of converting an address into geocoordinates and vice versa, respectively. Converting an address into coordinates allows us to visualize data on a map, measure distances, and check membership (seeing things such as what country, neighborhood, or school district an address belongs to).
This is actually a hard task, as it requires you to have a large hierarchical database of relevant addresses and a complex parsing engine to make sense of semi-structured, often misspelled and ambiguous, addresses. Realistically, a service like that requires a large investment of time and resources.
The good news is that we can use some...
