AGGREGATE world

#ENCODING
import io
import sys
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-16')
#MONGO
from pymongo import MongoClient
client = MongoClient()
client.progzoo.authenticate('scott','tiger')
db = client['progzoo']
#PRETTY
import pprint
pp = pprint.PrettyPrinter(indent=4)

Country Profile

For these questions you should use aggregate([]) on the collection world

Give the name and the per capita GDP for those countries with a population of at least 200 million.

per capita GDP is the GDP divided by the population.

pp.pprint(list(
    db.world.aggregate([
        {"$match":{
            "population":{"$gte":250000000}
        }},
        {"$project":{
            "_id":0,
            "name":1,
            "per capita GDP": {"$divide": ["$gdp",1000000]}
        }}
    ])
))

pp.pprint(list(db.world.aggregate([{"$match":{"population":{"$gte":200000000}}},{"$project":{"_id":0,"name":1,"per capita GDP": {"$divide": ["$gdp","$population"]}}}])))

Give the name and the population density of all countries. Ignore results where the density is "None".

population density is the population divided by the area

Use a $match. {"area":{"$ne":0}}

pp.pprint(list(
    db.world.aggregate([
        {"$project":{
            "_id":0,
            "name":1,
            "density": {"$divide": [10000,"$area"]}
        }},
        {"$match":{
            "density": {"$ne":None}
        }}
    ])
))

pp.pprint(list(db.world.aggregate([{"$match":{"area":{"$ne":0}}},{"$project":{"_id":0,"name":1,"density":{"$divide":["$population","$area"]}}},{"$match":{"density":{"$ne":None}}}])))