common_price

# -*- coding: utf-8 -*-
"""
Created on Wed Sep 20 10:51:47 2017

@author: Administrator
"""

import pymongo
from pymongo import MongoClient
import numpy as np
import pandas as  pd
from pandas import DataFrame,Series
from numpy import row_stack,column_stack
from dateutil.parser import parse
from matplotlib.pylab import date2num
import random


def commonprice(ct,rl):
    client1 = MongoClient('192.168.0.136',27017)
    db1 = client1.fangjia
    seaweed1 = db1.seaweed

    query1 = {"status":0,"cat":"district","city":ct,"region":rl}
    fields1 = {"lat2":1,"lng2":1, "city":1,"region":1,"cat":1,"name":1}

    lct= list()
    for s in seaweed1.find(query1, fields1):
        lct.append(s)

    lf=DataFrame(lct)
    print(lf)

    lk=list(lf['name'])


    #从公司的数据库中导入数据
    client = MongoClient('192.168.10.88',27777)
    db = client.fangjia
    seawater = db.seawater
    seawater.find_one()

    import random
    from collections import Counter    

    for i in range(len(lk)):
        query = {"city":ct,"cat":"sell","region":rl,
                 "district_name":lk[i],"p_date":{"$gt":20170701}}
        lt= seawater.count(query)
        #print(lt)
        pos = list()
        for s in seawater.find(query).limit(lt):
            pos.append(s)

        data=DataFrame(pos)

        if data.shape[0]>3:
            ppd=data[['total_price','area','district_name']]
            ppd1=ppd.dropna()

            avv=ppd1['total_price']/ppd1['area']
            #suma=ppd1['area'].values.sum()
            avv1=list(avv)
            avv2=(np.array(avv1)//2000)*2000
            #avp=int(avv.mean())
            mostn=Counter(avv2).most_common(1)
            mm=mostn[0][0]
            nn=mostn[0][1]
            print(mm,ppd1['district_name'][1],nn,rl)



            client1 = MongoClient('192.168.0.136',27017)
            db1 = client1.fangjia_stat
            stat = db1.district_stat
            stat.save({"city":ct,"region":rl,"district_name":ppd1['district_name'][1],
               "avg_price":mm, "weeedend":"2017-09-22","acuracy":nn})



cti=["上海"]

region_list=["黄浦","徐汇","长宁","虹口","静安","普陀",
             "杨浦","闵行","宝山","嘉定","浦东新","金山","松江",
              "青浦","奉贤"]    
for i in region_list:
    commonprice(cti[0],i)