流程

1.進入獲取疫情的url

例如：
騰訊新聞的疫情網站 https://news.qq.com/zt2020/page/feiyan.htm#/
網易新聞：https://wp.m.163.com/163/page/news/virus_report/index.html_nw_=1&anw=1

只需要找到網站的url以及user-agent后，進入url查看json數據格式，按照步驟即可訪問。
2.為了避免反爬，偽裝成瀏覽器：
找到headers = {‘user-agent’ : ‘Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.55’} ，進行瀏覽器訪問。
3.分析url，找到數據存放的規律
4.進行數據讀取和存儲

爬取全球最新疫情數據

import requests #爬取網頁 import json #json文件可以通過角標索引讀取內容 爬取json文件 import xlwings as xw #導入excel url = 'https://c.m.163.com/ug/api/wuhan/app/data/list-total?t=329822670771' #請求URL headers = {'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.55'} #瀏覽器訪問 response = requests.get(url , headers = headers) #print(response.status_code) #200表示訪問成功 #print(response.json()) # 打印內容wb = xw.Book() #相當于打開excel操作 sht = wb.sheets('sheet1') #相當于在excel里加了一個工作表 sht.range('A1').values = '地區' sht.range('B1').values = '新增確診' sht.range('C1').values = '累計確診' sht.range('D1').values = '死亡' sht.range('E1').values = '治愈' sht.range('F1').values = '日期'

在進入url分析數據格式后，將數據取出放入excel中。

json_data = response.json()['data']['areaTree'] #print(json_data) for i in range(206):earth_data = json_data[i]#print(earth_data)name = earth_data['name']sht.range(f'A{i+2}').value = nametoday_confirm = json.dumps(earth_data['today']['confirm'])sht.range(f'B{i+2}').value = today_confirmtotal_confirm = json.dumps(earth_data['total']['confirm'])sht.range(f'C{i+2}').value = total_confirmtotal_dead = json.dumps(earth_data['total']['dead'])sht.range(f'D{i+2}').value = total_deadtotal_heal = json.dumps(earth_data['total']['heal'])sht.range(f'E{i+2}').value = total_healdate = earth_data['lastUpdateTime']sht.range(f'F{i+2}').value = date#print("地區:"+name, "新增確診:"+today_confirm, "累計確診:"+total_confirm , "死亡"+total_dead,"治愈"+total_heal)

運行結果：

同理，爬取中國疫情歷史數據

import requests #爬取網頁 import json #爬取數據 import xlwings as xw #導入excel url = 'https://c.m.163.com/ug/api/wuhan/app/data/list-total?t=329822670771' headers = {'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.55'} response = requests.get(url , headers = headers) #print(response.status_code) #200表示訪問成功 #print(response.json()) # 打印內容wb = xw.Book() #相當于打開excel操作 sht = wb.sheets('sheet1') #相當于在excel里加了一個工作表 sht.range('A1').values = '地區' sht.range('B1').values = '新增確診' sht.range('C1').values = '累計確診' sht.range('D1').values = '死亡' sht.range('E1').values = '治愈' sht.range('F1').values = '日期' json_data = response.json()['data']['chinaDayList'] #print(json_data) for i in range(59):earth_data = json_data[i]#print(earth_data)#name = earth_data['name']#sht.range(f'A{i+2}').value = nametoday_confirm = json.dumps(earth_data['today']['confirm'])sht.range(f'B{i+2}').value = today_confirmtotal_confirm = json.dumps(earth_data['total']['confirm'])sht.range(f'C{i+2}').value = total_confirmtotal_dead = json.dumps(earth_data['total']['dead'])sht.range(f'D{i+2}').value = total_deadtotal_heal = json.dumps(earth_data['total']['heal'])sht.range(f'E{i+2}').value = total_healdate = earth_data['date']sht.range(f'F{i+2}').value = date#print("地區:"+name, "新增確診:"+today_confirm, "累計確診:"+total_confirm , "死亡"+total_dead,"治愈"+total_heal)

運行結果：

同理，爬取美國2020-2022年疫情歷史數據

import requests #爬取網頁 import json #爬取數據 import xlwings as xw #導入excel url = 'https://c.m.163.com/ug/api/wuhan/app/data/list-by-area-code?areaCode=7&t=1649117007316' headers = {'user-agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.55'} response = requests.get(url , headers = headers) wb = xw.Book() #相當于打開excel操作 sht = wb.sheets('sheet1') #相當于在excel里加了一個工作表 sht.range('A1').values = '地區' sht.range('B1').values = '新增確診' sht.range('C1').values = '累計確診' sht.range('D1').values = '死亡' sht.range('E1').values = '治愈' sht.range('F1').values = '日期' json_data = response.json()['data']['list'] #print(json_data) for i in range(772):earth_data = json_data[i]#print(earth_data)#name = earth_data['name']#sht.range(f'A{i+2}').value = nametoday_confirm = json.dumps(earth_data['today']['confirm'])sht.range(f'B{i+2}').value = today_confirmtotal_confirm = json.dumps(earth_data['total']['confirm'])sht.range(f'C{i+2}').value = total_confirmtotal_dead = json.dumps(earth_data['total']['dead'])sht.range(f'D{i+2}').value = total_deadtotal_heal = json.dumps(earth_data['total']['heal'])sht.range(f'E{i+2}').value = total_healdate = earth_data['date']sht.range(f'F{i+2}').value = date

運行結果：

爬取國內各省份疫情最新數據

import pandas as pd import requests import json def get_data():url = 'https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5'area = requests.get(url).json()data = json.loads(area['data'])update_time = data['lastUpdateTime']all_counties = data['areaTree']all_list = []for country_data in all_counties:if country_data['name'] != '中國':continueelse:all_provinces = country_data['children']for province_data in all_provinces:province_name = province_data['name']all_cities = province_data['children']for city_data in all_cities:city_name = city_data['name']city_total = city_data['total']province_result = {'province': province_name, 'city': city_name,'update_time': update_time}province_result.update(city_total)all_list.append(province_result)df = pd.DataFrame(all_list)df.to_csv('data.csv', index=False,encoding="utf_8_sig") get_data()

運行結果：

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總結

以上是生活随笔為你收集整理的python爬取疫情数据并存入excel中（包括国内各省份，全球，国内外历史疫情数据）代码可以直接运行的全部內容，希望文章能夠幫你解決所遇到的問題。

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