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Difference between revisions of "AGGREGATE examples"

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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 the name and population density of all countries. (population/area)</p>
+
<p class=strong>Show the name and population density of all Asian countries. (population/area)</p>
 
Note that "density" is a new field, made from the result of dividing two existing fields.
 
Note that "density" is a new field, made from the result of dividing two existing fields.
 
<div class=hint title="Dealing with division by 0">
 
<div class=hint title="Dealing with division by 0">

Revision as of 16:47, 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 population density of all Asian countries. (population/area)

Note that "density" is a new field, made from the result of dividing two existing fields.

To avoid diving by 0 we do a $match to remove any countries with negligible area, then pipe these results through to $project

pp.pprint(list(
     db.world.aggregate([
        {"$match":{"area":{"$ne":0},"continent":"Asia"}},
        {"$project":{
            "_id":0,
            "name":1,
            "density": {"$divide": ["$population","$area"]}
        }}
    ])
))

pp.pprint(list(db.world.aggregate([{"$match":{"area":{"$ne":0},"continent":"Asia"}},{"$project":{"_id":0,"name":1,"density":{"$divide":["$population","$area"]}}}])))