python爬取房产数据,在地图上展现

python爬取房产数据,在地图上展现

小伙伴,我又来了,这次我们写的是用python爬虫爬取乌鲁木齐的房产数据并展示在地图上,地图工具我用的是 BDP个人版-免费在线数据分析软件,数据可视化软件 ,这个可以导入csv或者excel数据。
首先还是分析思路,爬取网站数据,获取小区名称,地址,价格,经纬度,保存在excel里。再把excel数据上传到BDP网站,生成地图报表

本次我使用的是scrapy框架,可能有点大材小用了,主要是刚学完用这个练练手,再写代码前我还是建议大家先分析网站,分析好数据,再去动手写代码,因为好的分析可以事半功倍,乌鲁木齐楼盘,2017乌鲁木齐新楼盘,乌鲁木齐楼盘信息 - 乌鲁木齐吉屋网 这个网站的数据比较全,每一页获取房产的LIST信息,并且翻页,点进去是详情页,获取房产的详细信息(包含名称,地址,房价,经纬度),再用pipelines保存item到excel里,最后在bdp生成地图报表,废话不多说上代码:

JiwuspiderSpider.py
# -*- coding: utf-8 -*-
from scrapy import Spider,Request
import re
from jiwu.items import JiwuItem


class JiwuspiderSpider(Spider):
    name = "jiwuspider"
    allowed_domains = ["wlmq.jiwu.com"]
    start_urls = ['http://wlmq.jiwu.com/loupan']

    def parse(self, response):
        """
        解析每一页房屋的list
        :param response: 
        :return: 
        """
        for url in response.xpath('//a[@class="index_scale"]/@href').extract():
            yield Request(url,self.parse_html)  # 取list集合中的url  调用详情解析方法

        # 如果下一页属性还存在,则把下一页的url获取出来
        nextpage = response.xpath('//a[@class="tg-rownum-next index-icon"]/@href').extract_first()
        #判断是否为空
        if nextpage:
            yield Request(nextpage,self.parse)  #回调自己继续解析



    def parse_html(self,response):
        """
        解析每一个房产信息的详情页面,生成item
        :param response: 
        :return: 
        """
        pattern = re.compile('<script type="text/javascript">.*?lng = \'(.*?)\';.*?lat = \'(.*?)\';.*?bname = \'(.*?)\';.*?'
                             'address = \'(.*?)\';.*?price = \'(.*?)\';',re.S)
        item = JiwuItem()
        results = re.findall(pattern,response.text)
        for result in results:
            item['name'] = result[2]
            item['address'] = result[3]
            # 对价格判断只取数字,如果为空就设置为0
            pricestr =result[4]
            pattern2 = re.compile('(\d+)')
            s = re.findall(pattern2,pricestr)
            if len(s) == 0:
                item['price'] = 0
            else:item['price'] = s[0]
            item['lng'] = result[0]
            item['lat'] = result[1]
        yield item

item.py
# -*- coding: utf-8 -*-

# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html

import scrapy


class JiwuItem(scrapy.Item):
    # define the fields for your item here like:
    name = scrapy.Field()
    price =scrapy.Field()
    address =scrapy.Field()
    lng = scrapy.Field()
    lat = scrapy.Field()

    pass

pipelines.py 注意此处是吧mongodb的保存方法注释了,可以自选选择保存方式
# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html
import pymongo
from scrapy.conf import settings
from openpyxl import workbook

class JiwuPipeline(object):
    wb = workbook.Workbook()
    ws = wb.active
    ws.append(['小区名称', '地址', '价格', '经度', '纬度'])
    def __init__(self):
        # 获取数据库连接信息
        host = settings['MONGODB_URL']
        port = settings['MONGODB_PORT']
        dbname = settings['MONGODB_DBNAME']
        client = pymongo.MongoClient(host=host, port=port)

        # 定义数据库
        db = client[dbname]
        self.table = db[settings['MONGODB_TABLE']]

    def process_item(self, item, spider):
        jiwu = dict(item)
        #self.table.insert(jiwu)
        line = [item['name'], item['address'], str(item['price']), item['lng'], item['lat']]
        self.ws.append(line)
        self.wb.save('jiwu.xlsx')

        return item

最后报表的数据

mongodb数据库

地图报表效果图:BDP分享仪表盘,分享可视化效果

编辑于 2017-05-07

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