Target
- Count how many commodities are successfully trading in One day.
- Sort them by their Post Location.
- Draw a Pie chart to analyse the result.
** Tips: **
- Use aggregate function for advanced searching.
- Use the database given by teacher will be much easier.
** Why we use aggregate? **
Because it's much more effective than find() function.
Here we go
First, design a Pipeline to filter out the required data.
For example, if I would like to know how many goods were sold out one day in Beijing's different post location, And show them in a descending sort.
I can use this kind pipeline.
# get the goods sold in one day
pipeline = [
{'$match':{'$and':[{'pub_date':'2015.12.24'},{'time':1}]}},
{'$group':{'_id':{'$slice':['$area',0,1]},'counts':{'$sum':1}}},
{'$sort':{'counts':-1}}
]
PipeLine
Get other parameters ready
Parameters
Final charts and Full Code
Pie chart
import pymongo
import charts
client = pymongo.MongoClient('localhost', 27017)
myDB = client['ganjiDB']
myCollection = myDB['bjGanji']
# get the goods sold in one day
pipeline = [
{'$match':{'$and':[{'pub_date':'2015.12.24'},{'time':1}]}},
{'$group':{'_id':{'$slice':['$area',0,1]},'counts':{'$sum':1}}},
{'$sort':{'counts':-1}}
]
# Now prepare the series
dataSeries = []
for i in myCollection.aggregate(pipeline):
dataSeries.append([i['_id'][0],i['counts']])
print(dataSeries)
series = [
{
'type':'pie',
'name':'Counts',
'data':dataSeries
}
]
options = {
'chart':{'zoomType':'xy'},
'title':{'text':'Statics for Goods sold in One Day'},
'subtitle':{'text':'made by Jet'},
}
# Draw code
charts.plot(series,show='inline',options=options)
