1. 3. COVID-19 statistics from aggregated data from net site
   4. with Python
   5. Input from internet site: cases, recovered, deats.
   6. Calculates active cases.
   8. 12.01.2021
   9. 0000.0001

import math as math import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.ticker as ticker import locale from datetime import datetime, timedelta 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)
       
       

1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 2. main proge

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)]

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

df2 = selected_columns.copy()

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

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

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

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

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

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] if (dailycases1[n]<0): dailycases1[n]=0

for n in range(1,(len1-1)): dailydeaths1[n]=death1[n]-death1[n-1] if (dailydeaths1[n]<0): dailydeaths1[n]=0

fig, ax1 = plt.subplots(constrained_layout=True)

ax1.tick_params(axis='both', which='major', labelsize=15)

ax1.set_xlabel('Kuukausi', color='g',size=18) ax1.set_ylabel('Päivittäiset uudet tapaukset', color='#7f0000',size=18) ax1.set_title('Koronavirusepidemian 1. aalto Suomessa', color='b',size=22)

ax1.plot(dates_a,dailycases1, linewidth=2.5, color='#7f0000', label="Päivittäiset tapaukset")

ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis ax2.set_ylabel('Päivittäiset kuolemat', color='black',size=18) ax2.tick_params(axis='both', which='major', labelsize=15) ax2.plot(dates_a,dailydeaths1, linewidth=2, color='black',label="Päivittäiset kuolemat")

lines1, labels1 = ax1.get_legend_handles_labels() lines2, labels2 = ax2.get_legend_handles_labels()

ax2.legend(lines1 + lines2, labels1 + labels2, loc=0, fontsize=16)

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=';')