分析历史天气的趋势。

先采集

代码：

#-*- coding:utf-8 -*-import requestsimport randomimport MySQLdbimport xlwtfrom bs4 import BeautifulSoupuser_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.textindex_soup = BeautifulSoup(html_index)i = 1for href in index_soup.find("div",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("div",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 += 1myfile.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。