Difference between revisions of "AGGREGATE world"
From NoSQLZoo
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==Country Profile== | ==Country Profile== | ||
− | For these questions you should use aggregate([]) on the collection <code>world</code> | + | For these questions you should use <code>aggregate([])</code> on the collection <code>world</code> |
<div class='extra_space' style='width:1em; height:6em;'></div> | <div class='extra_space' style='width:1em; height:6em;'></div> | ||
<div class=q data-lang="py3"> | <div class=q data-lang="py3"> |
Revision as of 12:46, 16 July 2015
#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 GDP/population
The aggregation framework is a data processing pipeline. There are many operators that you can use.
$match
uses a query to limit or 'filter' what documents are to be used in the next stage of the pipeline.
$project
is used to "shape" documents by adding or removing fields. It also allows you to compare fields with the syntax $<fieldname>
pp.pprint(list( db.world.aggregate([ {"$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"]} }} ])
))