AGGREGATE examples: Difference between revisions
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<code>$project</code> Allows us to select what fields to display.<br/> | <code>$project</code> Allows us to select what fields to display.<br/> | ||
It can also has the ability to insert new fields and allows you to compare fields against each other without using <code>$where</code> | It can also has the ability to insert new fields and allows you to compare fields against each other without using <code>$where</code> | ||
<p class=strong>Show per capita GDP of all countries. (gdp/population)</p> | <p class=strong>Show the name and per capita GDP of all countries. (gdp/population)</p> | ||
<pre class=def> | <pre class=def> | ||
pp.pprint(list( | pp.pprint(list( | ||
Revision as of 13:15, 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)
Introducing the aggregation framework
These examples introduce the aggregation framework and its operators. Again we will be using the collection world
$match Allows us to perform queries in a similar way to find()
Show all the details for France
pp.pprint(list(
db.world.aggregate([
{"$match":{"name":"France"}}
])
))
pp.pprint(list(db.world.aggregate([{"$match":{"name":"France"}}])))
$project Allows us to select what fields to display.
It can also has the ability to insert new fields and allows you to compare fields against each other without using $where
Show the name and per capita GDP of all countries. (gdp/population)
pp.pprint(list(
db.world.aggregate([
{"$project":{
"_id":0,
"name":1,
"population":1,
"area":1,
"per capita GDP": {"$divide": ["$gdp","$population"]}
}}
])
))
pp.pprint(list(db.world.aggregate([{"$project":{"_id":0,"name":1,"population":1,"area":1,"per capita GDP": {"$divide": ["$gdp","$population"]}}}]) ))["$population","$area"]}}}])))