1. where the restaurant is not listed in the inspection data set.



db.restaurants.aggregate([
	{$lookup:
		{
			from: "inspections",
			localField: "",
			foriegnField: "",
			as: "restaurants_with_inspections"
		}
	},
	{$match:
		{"borough":"Manhattan","address.street":"Madison Avenue"}
	},
	{$sort:
		{"name":1}
	},
	{$project:
		{"_id":0, "restaurant_id":1, "name":1, "address.street":1}
	}
]).pretty()







2. for restaurants with evidence of mice or live mice (use violation code = “04L”)

in zipcodes that have a fifty-fifty split by gender (use percent female = “0.5”).


db.restaurants.aggregate([
	{$sort:
		{"borough":1, "name":1}
	},
	{$project:
		{"_id":0, "borough":1, "name":1, "restaurant_id":1}
	}
]).pretty()





3. write our own data demand/query