Python爬取全国最新房价信息保存为CSV文件,进行简单的数据分析

一、 使用Python爬取房价信息

1.话不多说先看代码

from bs4 import BeautifulSoup
import requests


class SpiderHours(object):
    def __init__(self):
        self.url = "http://www.creprice.cn/rank/cityforsale.html"
        self.headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36",
            "Cookie": "cityredata=1245960d33d174122151e3280a2630a2; city=sq; userchannel=EL-cityhouse; Hm_lvt_c2a7a3cec6f9dd8849155424efab19c7=1562643454,1562643606,1562644057; Hm_lpvt_c2a7a3cec6f9dd8849155424efab19c7=1562644057"}

    def request_page(self):
        response = requests.get(self.url, headers=self.headers)
        ret = response.content.decode("utf-8")
        soup = BeautifulSoup(ret, features="lxml")
        content = soup.find_all("th")
        temp_list = list()
        for info in content:  # 遍历数据
            temp_info = info.text.strip()  # 删除\n转义符
            temp_info = temp_info.replace(",", "")  # 删除数据中的","
            if len(temp_list) < 5:  # 整理数据
                temp_list.append(temp_info)
            else:
                with open("2019年全国房价.csv", "a") as f:  # 写入csv文件
                    f.write(",".join(temp_list) + "\n")
                    print(",".join(temp_list))
                temp_list = list()
                temp_list.append(temp_info)


if __name__ == '__main__':
    spider = SpiderHours()
    spider.request_page()

获取到的数据:

序号,城市名称,平均单价（元/㎡）,同比,环比
1,北京,63905,-0.23%,+0.2%
2,深圳,62987,+12.49%,+0.89%
3,上海,51877,-0.85%,-0.48%
4,厦门,45257,+2.61%,+1.84%
5,三亚,34185,-10.67%,-1.74%
6,广州,33858,+1.62%,+2.17%
7,南京,30540,+5.21%,-0.86%
8,杭州,30248,-6.3%,-4.26%
9,陵水,29052,-16.47%,-4.77%
10,福州,26145,-5.61%,-2.46%
…

进行数据分析-全国房价排名top30

好了今天就介绍到这里吧!