We already saw PyMongo using Python's client interface for MongoDB in the Executing query and insert operations using PyMongo and Executing update and delete operations using PyMongo recipes. In this recipe, we will use the postal code collection and run an aggregation example using PyMongo. The intention of this recipe is not to explain aggregation but to show how aggregation can be implemented using PyMongo. In this recipe, we will aggregate the data based on the state names and get the top five state names by the number of documents they appear in. We will make use of the $project, $group, $sort, and $limit operators for the process.
To execute the aggregation operations, we need to have a server up and running. A simple single node is what we will need. Refer to the Single node installation of MongoDB recipe in Chapter 1, Installing and Starting the MongoDB Server, to learn how to start the server. The data on which we will operate needs...