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python气温变化数据分析(基于python历史天气采集的分析)

时间:2022-03-28 12:33:06类别:脚本大全

python气温变化数据分析

基于python历史天气采集的分析

分析历史天气的趋势。

先采集

python气温变化数据分析(基于python历史天气采集的分析)

python气温变化数据分析(基于python历史天气采集的分析)

python气温变化数据分析(基于python历史天气采集的分析)

代码:

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  • #-*- coding:utf-8 -*-
  • import requests
  • import random
  • import mysqldb
  • import xlwt
  • from bs4 import beautifulsoup
  • user_agent=['mozilla/5.0 (windows nt 6.1; wow64) applewebkit/537.36 (khtml, like gecko) chrome/54.0.2840.87 safari/537.36',
  •     'mozilla/5.0 (x11; u; linux x86_64; zh-cn; rv:1.9.2.10) gecko/20100922 ubuntu/10.10 (maverick) firefox/3.6.10',
  •     'mozilla/5.0 (x11; linux x86_64) applewebkit/537.11 (khtml, like gecko) chrome/23.0.1271.64 safari/537.11',
  •     'mozilla/5.0 (windows nt 6.1; wow64) applewebkit/537.36 (khtml, like gecko) chrome/30.0.1599.101 safari/537.36',
  •     'mozilla/5.0 (windows nt 6.1; wow64) applewebkit/537.1 (khtml, like gecko) chrome/21.0.1180.71 safari/537.1 lbbrowser',
  •     'mozilla/5.0 (compatible; msie 9.0; windows nt 6.1; wow64; trident/5.0; slcc2; .net clr 2.0.50727; .net clr 3.5.30729; .net clr 3.0.30729; media center pc 6.0; .net4.0c; .net4.0e; qqbrowser/7.0.3698.400)',
  •     ]
  • headers={
  • 'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
  • 'accept-encoding': 'gzip, deflate, sdch',
  • 'accept-language': 'zh-cn,zh;q=0.8',
  • 'user-agent': user_agent[random.randint(0,5)]}
  •  
  • myfile=xlwt.workbook()
  • wtable=myfile.add_sheet(u"历史天气",cell_overwrite_ok=true)
  • wtable.write(0,0,u"日期")
  • wtable.write(0,1,u"最高温度")
  • wtable.write(0,2,u"最低温度")
  • wtable.write(0,3,u"天气")
  • wtable.write(0,4,u"风向")
  • wtable.write(0,5,u"风力")
  •  
  • db = mysqldb.connect('localhost','root','liao1234','liao',charset='utf8')
  • cursor = db.cursor()
  •  
  • index = requests.get("http://lishi.tianqi.com/binjianqu/index.html",headers=headers)
  • html_index = index.text
  • index_soup = beautifulsoup(html_index)
  • i = 1
  • for href in index_soup.find("li",class_="tqtongji1").find_all("a"):
  •   print href.attrs["href"]
  •  
  •  
  •   url = href.attrs["href"]
  •   r = requests.get(url,headers = headers)
  •   html = r.text
  •   #print html
  •   soup = beautifulsoup(html)
  •   ss = []
  •   s = []
  •   for tag in soup.find("li",class_="tqtongji2").find_all("li"):
  •     print tag.string
  •     s.append(tag.string)
  •     if len(s) == 6:
  •       ss.append(s)
  •       s = []
  •   flag = 0
  •   for s in ss:
  •     if flag == 0:
  •       flag = 1
  •       continue
  •     else:
  •       sql = "insert into weather(old_date,hight,low,weather,wind,wind_power) values('%s','%s','%s','%s','%s','%s')"%(s[0],s[1],s[2],s[3],s[4],s[5])
  •       cursor.execute(sql)
  •       wtable.write(i,0,s[0])
  •       wtable.write(i,1,s[1])
  •       wtable.write(i,2,s[2])
  •       wtable.write(i,3,s[3])
  •       wtable.write(i,4,s[4])
  •       wtable.write(i,5,s[5])
  •       i += 1
  • myfile.save("weather.xls")
  • db.close()
  • 以上这篇基于python历史天气采集的分析就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持开心学习网。

    原文链接:https://blog.csdn.net/qq1124794084/article/details/54174340

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