第三周大作业

交作业之前先写点感言。可以说是千疮百孔，没有第一第二周的突飞猛进，感觉知识很多，又都很生涩，非常不好理解和学习，自己想法很多都实现不了，有种小孩子刚开始学说话，着急表达不出来的感觉,挫败感很强。现在不知道是回头继续学习第三周还是继续先把第四周学完。

还是，学会导入 json 和到处 csv 文件。

import charts
import pymongo

client = pymongo.MongoClient('localhost',27017)
test = client['test']
item_info = test['item_info']

#{'area':[1,2,3]}# 城区是这样一个集合包含着列表的结构
pipeline = [
    {'$match':{'$and':[{'pub_date':{'$gte':'2015.12.01','$lte':'2016.01.04'}},{'area':{'$all':['海淀']}}]}},
    {'$group':{'_id':{'$slice':['$cates',2,1]},'counts':{'$sum':1}}},
    {'$limit':3}
]

for i in item_info.aggregate(pipeline):
    print(i)

def deta_gen(date1,date2,area,limit):
    pipeline1 = [
    {'$match':{'$and':[{'pub_date':{'$gte':date1,'$lte':date2}},{'area':{'$all':area}}]}},
    {'$group':{'_id':{'$slice':['$cates',2,1]},'counts':{'$sum':1}}},
    {'$limit':limit},
    {'$sort':{'counts':-1}}
]
    for i in item_info.aggregate(pipeline1):
        data = {
            'name':i['_id'][0],
            'data':[i['counts']],
            'type':'column'            
        }
        yield data
for i in deta_gen('2015.12.01','2016.01.04',['海淀'],3):
    print(i)

series = [i for i in deta_gen('2015.12.01','2016.01.04',['海淀'],6)]
options = {
    'chart':{'zoomType':'xy'},
    'title':{'text':'发帖数量最大类目'},
    'subtitle':{'text':'数据图表'},
    'yAxis':{'title':{'text':'数量'}}
    }
charts.plot(series,options=options,show='inline')

pipeline2 = [
    {'$match':{'$and':[{'pub_date':{'$gte':'2015.12.01','$lte':'2016.01.04'}},
                       {'cates':{'$all':['北京二手手机']}},
                       {'look':{'$nin':['-']}}
                      ]}},
    {'$group':{'_id':'$look','avg_price':{'$avg':'$price'}}},
    {'$sort':{'avg_price':-1}},
]
for i in item_info.aggregate(pipeline2):
    print(i)

def data_gen2(date1,date2,cates):
    pipeline = [
    {'$match':{'$and':[{'pub_date':{'$gte':date1,'$lte':date2}},
                       {'cates':{'$all':cates}},
                       {'look':{'$nin':['-']}}
                      ]}},
    {'$group':{'_id':'$look','avg_price':{'$avg':'$price'}}},
    {'$sort':{'avg_price':1}}
]
    for i in item_info.aggregate(pipeline):
        yield i['avg_price']

data = [i for i in data_gen2('2015.12.01','2016.01.04',['北京二手手机'])]
options = {
    'title':{'text':'新旧-价格'},
    'xAxis':{'categories':['报废机/尸体','7成新及以下','8成新','9成新','95成新','99成新', '全新']},
    'yAxis':{'title':{'text':'价格'}}
    }
charts.plot(data,options=options,show='inline')