Metadata-Version: 2.1
Name: scorecovid
Version: 0.0.3
Summary: A package for scoring policies of covid-19
Home-page: https://github.com/ytakefuji/score-covid-19-policy
Author: yoshiyasu takefuji
Author-email: takefuji@keio.jp
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/ytakefuji/score-covid-19-policy
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# score-covid-19-policy
You must create a file called countries for scoring individual policies of countries.

Country names must be separated by comma.
<pre>
$ cat countries
South Korea,India,Brazil,France,New Zealand,Taiwan,Sweden,Japan,United States,Canada,United Kingdom,Israel
</pre>

# How to install and run scorecovid
$ pip install scorecovid

$ scorecovid

# scorecovid.py
$ cat scorecovid.py
<pre>
import requests,re
import pandas as pd

def main():
 url='https://www.worldometers.info/world-population/population-by-country/'
 print('scraping population...')
 page=requests.get(url)
 df = pd.read_html(page.text)[0]
 df.columns.values[1]='Country'
 df.columns.values[2]='Population'
 #df = pd.read_html(page.text,flavor='html5lib')[0]
 df.to_csv('pop.csv')
 print('pop.csv was created')

 print('downloading total_deaths.csv file')
 import subprocess as sp
 sp.call("wget https://github.com/owid/covid-19-data/raw/master/public/data/jhu/total_deaths.csv",shell=True)
 p=pd.read_csv('total_deaths.csv')

#
#from urllib.request import Request, urlopen
#url='https://www.worldometers.info/coronavirus/#nav-today/'
#print('scraping deaths informationi...')
#req = Request(url, headers={'User-Agent': 'Firefox/76.0.1'})
#page = re.sub(r'<.*?>', lambda g: g.group(0).upper(), urlopen(req).read().decode('utf-8') )
#df = pd.read_html(page)[0]
#df.to_csv('deaths.csv')
#print('deaths.csv was created')
#


 print('countries file was read...')
 d=open('countries').read().strip()
 print('scoring the following ',len(d),' countries...')
 d=d.split(',')
 print(d)

 dd=pd.DataFrame(
  { "country": d,
   "deaths": range(len(d)),
   "population": range(len(d)),
   "score": range(len(d)),
  })
 
 pp=pd.read_csv('pop.csv')
 print('calculating scores of countries\n')
 print('score is created in result.csv')
 
 for i in d:
 # print(p[i][len(p)-1])
  dd.loc[dd.country==i,'deaths']=int(p[i][len(p)-1])
 # print(pp.loc[pp.Country==i,'Population'])
  dd.loc[dd.country==i,'population']=int(pp.loc[pp.Country==i,'Population']/1000000)
  dd.loc[dd.country==i,'score']=int(dd.loc[dd.country==i,'deaths']/dd.loc[dd.country==i,'population'])
 dd=dd.sort_values(by=['score'])
 print(dd)
 dd.to_csv('result.csv')
 print('pop.csv and total_deaths.csv were removed')
 sp.call("rm total_deaths.csv pop.csv",shell=True)

if __name__ == "__main__":
 main()

</pre>


