Difference between revisions of "AGGREGATE world"
| Line 148: | Line 148: | ||
</div> | </div> | ||
| − | + | ==Harder Questions== | |
<div class=q data-lang="py3"> | <div class=q data-lang="py3"> | ||
| − | + | Using Conditions<br/> | |
| − | < | + | <code>$cond</code> is similar to a <code>CASE</code> statement in other languages.<br/> |
| − | + | It has the form <code>"$cond": [{<comparison> :[<field or value>,<field or value>]},<true case>,<false case>]</code><br/> | |
| − | </ | + | Using <code>$cond</code>, reattempt the above question but change <b>Eurasia</b> to <b>Europe</b> |
<pre class=def> | <pre class=def> | ||
pp.pprint(list( | pp.pprint(list( | ||
db.world.aggregate([ | db.world.aggregate([ | ||
{"$group":{ | {"$group":{ | ||
| − | "_id":"$ | + | "_id":{ |
| − | "area":{"$ | + | "$cond": [{"$eq" :["$continent","Eurasia"]},"Europe","$continent"] |
| + | }, | ||
| + | "area":{"$sum": "$area"} | ||
}}, | }}, | ||
{"$sort":{ | {"$sort":{ | ||
| Line 175: | Line 177: | ||
db.world.aggregate([ | db.world.aggregate([ | ||
{"$group":{ | {"$group":{ | ||
| − | "_id":"$continent", | + | "_id":{ |
| + | "$cond": [{"$eq" :["$continent","Eurasia"]},"Europe","$continent"] | ||
| + | }, | ||
"area":{"$sum": "$area"} | "area":{"$sum": "$area"} | ||
}}, | }}, | ||
Revision as of 13:21, 17 July 2015
#ENCODING
import io
import sys
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-16')
#MONGO
from pymongo import MongoClient
client = MongoClient()
client.progzoo.authenticate('scott','tiger')
db = client['progzoo']
#PRETTY
import pprint
pp = pprint.PrettyPrinter(indent=4)
Country Profile
For these questions you should use aggregate([]) on the collection world
Give the name and the per capita GDP for those countries with a population of at least 200 million.
per capita GDP is the GDP divided by the population.
pp.pprint(list(
db.world.aggregate([
{"$match":{
"population":{"$gte":250000000}
}},
{"$project":{
"_id":0,
"name":1,
"per capita GDP": {"$divide": ["$gdp",1000000]}
}}
])
))
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":{"$ne":None}}}])))
Show the name and population in millions for the countries of the continent South America. Divide the population by 1000000 to get population in millions.
pp.pprint(list(
db.world.aggregate([
{"$match":{
}},
{"$project":{
"_id":0,
"name":1
}}
])
))
pp.pprint(list(db.world.aggregate([{"$match":{"continent":{"$eq":"South America"}}},{"$project":{"_id":0,"name":1,"population":{"$divide":["$population",1000000]}}}])))
Show the name and population density for France, Germany, and Italy
pp.pprint(list(
db.world.aggregate([
{"$match":{
"name": {"$in":['United Kingdom','United States','Brazil']},
"population": {"$ne": None},
"area": {"$ne": 0}
}},
{"$project":{
"_id":0,
"name":1
}}
])
))
pp.pprint(list(db.world.aggregate([{"$match":{"name":{"$in":['France','Germany','Brazil']},"population":{"$ne":None},"area":{"$ne":0}}},{"$project":{"_id":0,"name":1,"population density":{"$divide":["$population","$area"]}}}])))
Order the continents by area from most to least.
pp.pprint(list(
db.world.aggregate([
{"$group":{
"_id":"$name",
"area":{"$max": "$area"}
}},
{"$sort":{
"area": -1
}},
{"$project":{
"_id":1,
"area":1
}}
])
))
pp.pprint(list(
db.world.aggregate([
{"$group":{
"_id":"$continent",
"area":{"$sum": "$area"}
}},
{"$sort":{
"area": -1
}},
{"$project":{
"_id":1,
"area":1
}}
])
))
Harder Questions
Using Conditions
$cond is similar to a CASE statement in other languages.
It has the form "$cond": [{<comparison> :[<field or value>,<field or value>]},<true case>,<false case>]
Using $cond, reattempt the above question but change Eurasia to Europe
pp.pprint(list(
db.world.aggregate([
{"$group":{
"_id":{
"$cond": [{"$eq" :["$continent","Eurasia"]},"Europe","$continent"]
},
"area":{"$sum": "$area"}
}},
{"$sort":{
"area": -1
}},
{"$project":{
"_id":1,
"area":1
}}
])
))
pp.pprint(list(
db.world.aggregate([
{"$group":{
"_id":{
"$cond": [{"$eq" :["$continent","Eurasia"]},"Europe","$continent"]
},
"area":{"$sum": "$area"}
}},
{"$sort":{
"area": -1
}},
{"$project":{
"_id":1,
"area":1
}}
])
))