#-coding:utf-8
# author: 钟子龙
# 爬取中国天气网华北地区今日天气
import requests
from bs4 import BeautifulSoup
from pyecharts import Bar
ALL_DATA = []
def parse_page(url):
headers = {
'User-Agent': "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.113 Safari/537.36"
}
response = requests.get(url, headers=headers)
text = response.content.decode('utf-8')
# html5ilb有很高的容错性,如果有标签缺失,它就会自动补齐
# pip install html5lib
soup = BeautifulSoup(text,'html5lib')
conMidtab = soup.find('div',class_='conMidtab')
tables = conMidtab.find_all('table')
for table in tables:
trs = table.find_all('tr')[2:]
for index,tr in enumerate(trs):
tds = tr.find_all('td')
# 获取城市
city_td = tds[0]
# 获取最低气温
temp_td = tds[-2]
# 获取天气状况
weather_td = tds[1]
if index == 0:
city_td = tds[1]
weather_td = tds[2]
city = list(city_td.stripped_strings)[0]
min_temp = list(temp_td.stripped_strings)[0]
weather = list(weather_td.stripped_strings)[0]
ALL_DATA.append({"city":city,"min_temp":int(min_temp),"weather":weather})
# print({"city":city,"min_temp":int(min_temp),"weather":weather})
def main():
# 创建url池,表示不同地区的url
urls = [
'http://www.weather.com.cn/textFC/hb.shtml',
'http://www.weather.com.cn/textFC/db.shtml',
'http://www.weather.com.cn/textFC/hd.shtml',
'http://www.weather.com.cn/textFC/hz.shtml',
'http://www.weather.com.cn/textFC/hn.shtml',
'http://www.weather.com.cn/textFC/xb.shtml',
'http://www.weather.com.cn/textFC/xn.shtml',
'http://www.weather.com.cn/textFC/gat.shtml'
]
for url in urls:
parse_page(url)
# 根据最低气温进行排序
ALL_DATA.sort(key=lambda data:data['min_temp'])
data= ALL_DATA[0:10]
cities = list(map(lambda x:x['city'],data))
temps = list(map(lambda x:x['min_temp'],data))
# 取前面十个
# 可视化pyecharts pip install pyecharts
# 但是目前的pyecharts与1.0版本一下的不一样,有一些方法不同,需要还原为0.1.9.4
chart = Bar('中国最低气温')
chart.add('',cities,temps)
chart.render('temperature.html')
if __name__ == '__main__':
main()
Python爬取中国天气网天气数据并可视化
最新推荐文章于 2025-04-08 16:50:47 发布