Python 疫情数据的可视化与分析（一）

疫情数据的可视化

对疫情地图的数据的抓取与可视化词云显示，采用百度地图数据https://voice.baidu.com/act/newpneumonia/newpneumonia

第一弹数据获取：

可以打印出url网页数据信息

import requests
import json
from lxml import etree
import openpyxl

url = "https://voice.baidu.com/act/newpneumonia/newpneumonia"
response = requests.get(url)
print(response.text)

查看url的网页源代码，用ctr+f 快速查找 可以看到数据文件的格式以application/json 开头

而且以component的caseList里开始才有疫情数据

通过获取URL的component对象里的caseList转换成json数据

html = etree.HTML(response.text)
result = html.xpath(//script[@type="application/json"]/text())
result = result[0]
result = json.loads(result)
# print(result[component][0][globalList])
result1 = result[component][0][caseList]
for each in result1:
    print(each)
    print(* * 50 + 
)

储存到excel中

# 创建工作簿
wb = openpyxl.Workbook()
# 创建工作表
ws = wb.active
ws.title = "国内疫情"
ws.append([省份, 累计确诊, 死亡, 治愈, 现有确诊, 累计确诊, 死亡增量, 治愈增量, 现有确诊增量])
for each in result1:
    temp_list = [each[area], each[confirmed], each[died], each[crued], each[relativeTime], each[confirmedRelative], each[diedRelative], each[curedRelative], each[curConfirmRelative]]
    for i in range(len(temp_list)):
      if temp_list[i] == :
          temp_list[i] = 0
    ws.append(temp_list)

wb.save(./data.xlsx)

结果如下data.xls 将代码改成国外的获取数据获取globalList

result2 = result[component][0][globalList]
for each in result2:
    print(each)
    print(* * 50 + 
)

# 创建工作簿
wb = openpyxl.Workbook()
# 创建工作表
ws = wb.active
ws.title = "国内疫情"
ws.append([省份, 累计确诊, 死亡, 治愈, 现有确诊    , 累计确诊])
for each in result2:
    temp_list = [each[area], each[confirmed], each[died], each[crued], each[confirmedRelative], each[curConfirm]]
    for i in range(len(temp_list)):
      if temp_list[i] == :
          temp_list[i] = 0
    ws.append(temp_list)

wb.save(./data1.xlsx)

将给州的数据分隔，在每个数据里有subList

比如说{area: 欧洲, subList: [{died: 52, confirmed: 2629, crued: 1535,

result2 = result[component][0][globalList]
for each in result2:
    print(each)
    print(* * 50 + 
)

# 创建工作簿
wb = openpyxl.Workbook()
# 创建工作表
ws = wb.active
ws.title = "国内疫情"
ws.append([省份, 累计确诊, 死亡, 治愈, 现有确诊    , 累计确诊])
for each in result2:
    temp_list = [each[area], each[confirmed], each[died], each[crued], each[confirmedRelative], each[curConfirm]]
    for i in range(len(temp_list)):
      if temp_list[i] == :
          temp_list[i] = 0
    ws.append(temp_list)
for each in result2:
    sheet_title = each[area]
    # 创建新的工作表
    ws_out = wb.create_sheet(sheet_title)
    ws_out.append([国家, 累计确诊, 死亡, 治愈, 现有确诊    , 累计确诊])
    for country in each[subList]:
        temp_list = [country[country], country[confirmed], country[died], country[crued], country[confirmedRelative], country[curConfirm]]
        ws_out.append(temp_list)


wb.save(./data1.xlsx)

结果如图 好了数据清洗就告一段落了。疫情的词云分析请看接下来的博文 。