Python疫情数据可视化

1 课题介绍

全球Covid-19大危机影响我们的生活，我们的出行、交流、教育、经济等都发生了巨大的变化，全球疫情大数据可视化分析与展示，可用于社会各界接入疫情数据，感知疫情相关情况的实时交互式态势，是重要的疫情分析、防控决策依据。

我国爆发的疫情，对我们的日常生活带来了极大的影响，疫情严重期间，大家都谈“疫”色变，大家对于了解疫情的情况具有巨大的需求；

代码在最下面（要的请私）

Python+SpringBoot+Vue

2 运行效果

3 关键代码

3.1 数据爬虫

疫情数据爬虫，就是给网站发起请求，并从响应中提取需要的数据

1、发起请求，获取响应

• 通过http库，对目标站点进行请求。等同于自己打开浏览器输入网址
• 常用库：urllib、requests
• 服务器会返回请求的内容一般为：HTML、文档、JSON字符串等

2、解析内容

• 寻找自己需要的信息，也就是利用正则表达式或者其他库提取目标信息
• 常用库：re、beautifulsoup4

3、保存数据

• 将解析到的数据持久化到数据库中

import pymysql
import time 
import json
import traceback  #追踪异常
import requests
def get_tencent_data(): 
    """
    :return: 返回历史数据和当日详细数据
    """
    url = ''
    url_his=''
    #最基本的反爬虫
    headers = {
        'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.88 Safari/537.36',
    }
    r = requests.get(url, headers)	#使用requests请求
    res = json.loads(r.text)  # json字符串转字典
    data_all = json.loads(res['data'])
#再加上history的配套东西
r_his=requests.get(url_his,headers)
res_his=json.loads(r_his.text)
data_his=json.loads(res_his['data'])

history = {}  # 历史数据
for i in data_his["chinaDayList"]:
    ds = "2020." + i["date"]
    tup = time.strptime(ds, "%Y.%m.%d")
    ds = time.strftime("%Y-%m-%d", tup)  # 改变时间格式,不然插入数据库会报错，数据库是datetime类型
    confirm = i["confirm"]
    suspect = i["suspect"]
    heal = i["heal"]
    dead = i["dead"]
    history[ds] = {"confirm": confirm, "suspect": suspect, "heal": heal, "dead": dead}
for i in data_his["chinaDayAddList"]:
    ds = "2020." + i["date"]
    tup = time.strptime(ds, "%Y.%m.%d")
    ds = time.strftime("%Y-%m-%d", tup)
    confirm = i["confirm"]
    suspect = i["suspect"]
    heal = i["heal"]
    dead = i["dead"]
    history[ds].update({"confirm_add": confirm, "suspect_add": suspect, "heal_add": heal, "dead_add": dead})
    
details = []  # 当日详细数据
update_time = data_all["lastUpdateTime"]
data_country = data_all["areaTree"]  # list 25个国家
data_province = data_country[0]["children"]  # 中国各省
for pro_infos in data_province:
    province = pro_infos["name"]  # 省名
    for city_infos in pro_infos["children"]:
        city = city_infos["name"]
        confirm = city_infos["total"]["confirm"]
        confirm_add = city_infos["today"]["confirm"]
        heal = city_infos["total"]["heal"]
        dead = city_infos["total"]["dead"]
        details.append([update_time, province, city, confirm, confirm_add, heal, dead])
return history, details

• 数据表结构

  history表存储每日的总数据

  CREATE TABLE history (
  ds datetime NOT NULL COMMENT ‘日期’,
  confirm int(11) DEFAULT NULL COMMENT ‘累计确诊’,
  confirm_add int(11) DEFAULT NULL COMMENT ‘当日新增确诊’,
  suspect int(11) DEFAULT NULL COMMENT ‘剩余疑似’,
  suspect_add int(11) DEFAULT NULL COMMENT ‘当日新增疑似’,
  heal int(11) DEFAULT NULL COMMENT ‘累计治愈’,
  heal_add int(11) DEFAULT NULL COMMENT ‘当日新增治愈’,
  dead int(11) DEFAULT NULL COMMENT ‘累计死亡’,
  dead_add int(11) DEFAULT NULL COMMENT ‘当日新增死亡’,
  PRIMARY KEY (ds) USING BTREE ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
  
    
       
       
       
       
  
    
       
       
       
       
  
        
        
        
        
  details表存储每日的详细数据
   
  
     
  CREATE TABLE details (
  id int(11) NOT NULL AUTO_INCREMENT,
  update_time datetime DEFAULT NULL COMMENT ‘数据最后更新时间’,
  province varchar(50) DEFAULT NULL COMMENT ‘省’,
  city varchar(50) DEFAULT NULL COMMENT ‘市’,
  confirm int(11) DEFAULT NULL COMMENT ‘累计确诊’,
  confirm_add int(11) DEFAULT NULL COMMENT ‘新增确诊’,
  heal int(11) DEFAULT NULL COMMENT ‘累计治愈’,
  dead int(11) DEFAULT NULL COMMENT ‘累计死亡’,
  PRIMARY KEY (id) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
  
      
          
          
          
          
  
      
          
          
          
          
  
           
           
           
           
  整体的数据库图表：
   
   
  
       
  3.2 可视化部分
   
  
       
  echarts绘制图表
   
  
       
  def get_c1_data():
      """
      :return: 返回大屏div id=c1 的数据
      """
      # 因为会更新多次数据，取时间戳最新的那组数据
      sql = "select sum(confirm)," \
            "(select suspect from history order by ds desc limit 1)," \
            "sum(heal)," \
            "sum(dead) " \
            "from details " \
            "where update_time=(select update_time from details order by update_time desc limit 1) "
      res = query(sql)
      res_list = [str(i) for i in res[0]]
      res_tuple=tuple(res_list)
      return res_tuple
  
      
          
          
          
          
    
       
       
       
       

• 中国疫情地图实现

  def get_c2_data():
      """
      :return:  返回各省数据
      """
      # 因为会更新多次数据，取时间戳最新的那组数据
      sql = "select province,sum(confirm) from details " \
            "where update_time=(select update_time from details " \
            "order by update_time desc limit 1) " \
            "group by province"
      res = query(sql)
      return res
  

全国累计趋势

def get_l1_data():
	"""
	:return:返回每天历史累计数据
	"""
    sql = "select ds,confirm,suspect,heal,dead from history"
    res = query(sql)
    return res

def get_l2_data():
“”"
:return:返回每天新增确诊和疑似数据
“”"
sql = “select ds,confirm_add,suspect_add from history”
res = query(sql)
return res

def get_r1_data():
“”"
:return: 返回非湖北地区城市确诊人数前5名
“”"
sql = 'SELECT city,confirm FROM ‘
’(select city,confirm from details '
'where update_time=(select update_time from details order by update_time desc limit 1) '
'and province not in (“湖北”,“北京”,“上海”,“天津”,“重庆”) '
'union all '
'select province as city,sum(confirm) as confirm from details '
'where update_time=(select update_time from details order by update_time desc limit 1) '
'and province in (“北京”,“上海”,“天津”,“重庆”) group by province) as a '
‘ORDER BY confirm DESC LIMIT 5’
res = query(sql)
return res

• 疫情热搜

  def get_r2_data():
      """
      :return:  返回最近的20条热搜
      """
      sql = 'select content from hotsearch order by id desc limit 20'
      res = query(sql)  # 格式 (('民警抗疫一线奋战16天牺牲1037364',), ('四川再派两批医疗队1537382',)
      return re
  

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