1. 2. COVID-19 statistics from aggregated data from net site
   3. with Python
   4. Input from internet site: cases, recovered, deats.
   5. Calculates active cases.
   7. 12.1.2021
   8. 0002.0001

import math as math import numpy as np import pandas as pd import matplotlib.pyplot as plt

import locale from datetime import datetime, timedelta

import matplotlib.ticker as ticker import matplotlib.dates as mdates from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,

                              AutoMinorLocator)

def format_func(value, tick_number):

   N = int(np.round(value/10))
   if N == 0:
       return "0"
   else:
       return r"${0}\pv$".format(N)
       
       

dfin = pd.read_csv('https://datahub.io/core/covid-19/r/countries-aggregated.csv', parse_dates=['Date']) countries = ['Finland'] dfin = dfin[dfin['Country'].isin(countries)]

1. print(dfin)

1. quit()

selected_columns = dfin"Date", "Confirmed", "Recovered", "Deaths"

df2 = selected_columns.copy()

df2.to_csv (r'kovadata1.csv', index = True, header=True, sep=';')

1. 1. sektion 2
      1. draw estimeted active cases, smoothed

df = pd.read_csv(r'kovadata1.csv', delimiter=';')

1. print (df["Date"])

dates=df['Date'] locale.setlocale(locale.LC_TIME, "fi_FI") dates_a = [datetime.strptime(d,'%Y-%m-%d').date() for d in dates]

len1=len(df["Date"]) aktiv2= [None] * len1 for n in range(0,len1-1): aktiv2[n]=0

1. print( len1)

1. index1=df['Index']

dates=df['Date'] rekov1=df['Recovered'] konf1=df['Confirmed'] death1=df['Deaths']

spanni=6

rulla = rekov1.rolling(window=spanni).mean() rulla2 = rulla.rolling(window=spanni).mean() tulosrulla=rulla2

1. print (rulla)

x=np.linspace(0,len1,len1);

for n in range(0,(len1-1)): rulla2[n]=round(tulosrulla[n],0) aktiv2[n]=konf1[n]-death1[n]-rulla2[n]

dailycases1= [0] * len1 dailydeaths1= [0] * len1

for n in range(1,(len1-1)): dailycases1[n]=konf1[n]-konf1[n-1]

for n in range(1,(len1-1)): dailydeaths1[n]=death1[n]-death1[n-1]

fig, ax = plt.subplots(constrained_layout=True)

ax.legend(fontsize=14)

secax = ax.secondary_xaxis('top')

1. secax.set_xlabel('paivia')

dates2= [None] * len1 dates3= [None] * (int(len1/10)+1)

plt.xticks(fontsize=14)

plt.yticks(fontsize=14, rotation=0)

ax.set_xlabel('pvm', color='g',size=18) ax.set_ylabel('luku', color='g',size=18) ax.set_title('Koronavirusepidemia', color='b',size=22)

1. ax.plot(x, rekov1,'g-',linewidth=4.0, label='parantuneita')
2. ax.plot(x, aktiv2,'r-',linewidth=4.0, label='sairaana')
3. ax.plot(x, death1,'k-',linewidth=4.0, label='kuolleita')
4. ax.plot(x, konf1,'y.-',linewidth=4.0, label='tapauksia')

ax.plot(dates_a, rekov1,'g-',linewidth=4.0, label='parantuneita') ax.plot(dates_a, aktiv2,'r-',linewidth=4.0, label='sairaana') ax.plot(dates_a, death1,'k-',linewidth=4.0, label='kuolleita') ax.plot(dates_a, konf1,'y.-',linewidth=4.0, label='tapauksia')

dateformat1 = mdates.DateFormatter('%d.%m')

ax.xaxis.set_major_formatter(dateformat1)

ax.legend(fontsize=14)

plt.show()

plt.savefig('kuva.svg')

for n in range(0,(len1-1)): luku0=aktiv2[n] luku1=luku0.astype(float) if(math.isnan(luku0)): aktiv2[n]=0

aktiv2[len1-1]=0

aktiv3a = np.array(aktiv2)

1. print(aktiv2)

1. print(aktiv3a)

aktiv3=aktiv3a.astype(int)

1. print(aktiv3)

print(df)

1. df.drop(1, axis=1)

df.insert (2, "Daily_Cases", dailycases1) df.insert (3, "Daily_Deaths", dailydeaths1)

1. quit()

df['ActiveEst']=aktiv3

dfout = df'Date', 'Confirmed','Deaths','Recovered', 'ActiveEst','Daily_Cases','Daily_Deaths'

print(dfout) dfout.to_csv (r'kovadata2.csv', index = True, header=True, sep=';')