text: import pandas as pd
  import io
  import requests
  import numpy as np
  from matplotlib import pyplot as plt
  import datetime
  url="https://raw.githubusercontent.com/yuval-harpaz/covid-19-israel-matlab/master/data/Israel/dashboard_timeseries.csv"
  s = requests.get(url).content
  dashboard = pd.read_csv(io.StringIO(s.decode('utf-8')))
  url="https://raw.githubusercontent.com/yuval-harpaz/covid-19-israel-matlab/master/data/Israel/positive_to_death.txt"
  s = requests.get(url).content
  probability = pd.read_csv(io.StringIO(s.decode('utf-8')))
  url="https://raw.githubusercontent.com/yuval-harpaz/covid-19-israel-matlab/master/data/Israel/tests.csv"
  s = requests.get(url).content
  tests = pd.read_csv(io.StringIO(s.decode('utf-8')))
  #  Moving average smoothiong
  N = 7
  fm = tests.pos_f_60+tests.pos_m_60
  pos60 = np.convolve(fm, np.ones((N,))/N, mode='valid')
  pos60 = np.concatenate(([0,0,0],pos60))
  for i_end in [6,5,4]:
      pos60 = np.concatenate((pos60,[np.mean(fm[-i_end:])]))
  
  dead = np.convolve(dashboard.CountDeath, np.ones((N,))/N, mode='valid')
  dead[0:19] = 0
  dead = np.concatenate(([0,0,0],dead))
  
  for i_end in [6,5,4]:
      dead = np.concatenate((dead,[np.mean(dashboard.CountDeath[-i_end:])]))
  
  # predict
  pred = np.convolve(pos60, probability['all'], mode='full')
  # plot
  date_test = [datetime.datetime.strptime(tests['date'][0], '%d-%b-%Y')]
  for iDate in range(len(pred)-1):
      date_test.append(date_test[-1] + datetime.timedelta(days=1))
  date_dash = [datetime.datetime.strptime(dashboard['date'][0], '%d-%b-%Y')]
  for iDate in range(len(dead)-1):
      date_dash.append(date_dash[-1] + datetime.timedelta(days=1))
  
                                              
  fig, axs = plt.subplots()
  plt.plot(date_test,pred/10, label='predicted deaths')
  plt.plot(date_dash,dead, label='deaths (7 day smoothing)')
  plt.xticks(rotation=45)
  plt.legend()
  plt.suptitle('Daily deaths prediction in Israel by positive tests for over 60y')
  plt.ylabel('Deaths')
  plt.grid()
  plt.show()
  