fjw计算均价

# -*- coding: utf-8 -*-"""Created on Thu Aug 24 15:14:07 2017@author: Administrator"""import pymongofrom pymongo import MongoClientimport numpy as npimport pandas as  pdfrom pandas import DataFrame,Seriesfrom numpy import row_stack,column_stackfrom dateutil.parser import parsefrom matplotlib.pylab import date2numimport random#导入经度和纬度,把经纬度转化成DataFrameclient1 = MongoClient('192.168.0.136',27017)db1 = client1.fangjiaseaweed1 = db1.seaweed#print(seaweed.find_one({"city":"上海","region":"浦东","name":"康桥半岛二期"},{"lat2":1,"lng2":1}))cy_rg=["成都","锦江"]query1 = {"status":0,"cat":"district","city":cy_rg[0],"region":cy_rg[1]}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)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.fangjiaseawater = db.seawaterseawater.find_one()# 索引数据库里的数据for i in range(len(lk)):    query = {"city":cy_rg[0],"cat":"sell","region":cy_rg[1],             "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=ppd['total_price']/ppd['area']        #suma=ppd1['area'].values.sum()        avp=int(avv.mean())        print(avp,ppd1['district_name'][1])        client1 = MongoClient('192.168.0.136',27017)        db1 = client1.fangjia_stat        stat = db1.district_stat        stat.save({"city":cy_rg[0],"region":cy_rg[1],"district_name":ppd1['district_name'][1],           "avg_price":avp, "weeedend":"2017-09-08"})