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https://github.com/tikazyq/mondas
pandas over mongo
https://github.com/tikazyq/mondas
Last synced: 26 days ago
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pandas over mongo
- Host: GitHub
- URL: https://github.com/tikazyq/mondas
- Owner: tikazyq
- Created: 2014-03-29T00:31:40.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2014-06-08T20:53:52.000Z (over 10 years ago)
- Last Synced: 2023-08-21T00:15:49.425Z (about 1 year ago)
- Language: Python
- Size: 180 KB
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
mondas
======
pandas: https://pypi.python.org/pypi/pandas#downloads
pymongo: http://api.mongodb.org/python/current/installation.html
mongodb: http://www.mongodb.org/downloads
Examples
======
The examples below will work on zip code data set provided by mongodb.org. Please follow the guide to import into mongodb.
Link: http://docs.mongodb.org/manual/tutorial/aggregation-zip-code-data-set/
A simple query to the database.
```python
from mondas import Mongo
m = Mongo()
# m.set_connection('localhost') # default 'localhost'
# m.set_db('test') # default 'test'
m.set_col('zips')
m.add_query({'state': 'NY'})
m.add_project({'state': 1, 'pop': 1, 'city': 1})
m.run()
print(m.res[:10])
_id city pop state
0 06390 FISHERS ISLAND 329 NY
1 10001 NEW YORK 18913 NY
2 10002 NEW YORK 84143 NY
3 10003 NEW YORK 51224 NY
4 10004 GOVERNORS ISLAND 3593 NY
5 10005 NEW YORK 202 NY
6 10006 NEW YORK 119 NY
7 10007 NEW YORK 3374 NY
8 10009 NEW YORK 57426 NY
9 10010 NEW YORK 24907 NY
```
mongo shell equavalent
```javascript
db.zips.find({state: 'NY'}, {state:1, pop:1, city:1});
```
Aggregation example: find top 10 cities with most population
```python
from mondas import AggregationFramework
ag = AggregationFramework()
# ag.set_connection('localhost') # default 'localhost'
# ag.set_db('test') # default 'test'
ag.set_col('zips')
ag.add_group({
'_id': {
'city': '$city',
'state': '$state'
},
'pop': {'$sum': '$pop'}
})
ag.add_sort({'pop': -1})
ag.add_limit(10)
ag.run()
print(ag.res)
city state pop
0 CHICAGO IL 2452177
1 BROOKLYN NY 2300504
2 LOS ANGELES CA 2102295
3 HOUSTON TX 2095918
4 PHILADELPHIA PA 1610956
5 NEW YORK NY 1476790
6 BRONX NY 1209548
7 SAN DIEGO CA 1049298
8 DETROIT MI 963243
9 DALLAS TX 940191
```
mongo shell equivalent
```javascript
var res = db.zips.aggregate(
{
$group: {
_id: {
city: '$city',
state: '$state'
},
pop: {$sum: '$pop'}
}
},
{
$sort: {pop: -1}
},
{
$limit: 10
})['result'];
printjson(res);
```