Small script to plot data from the Johns Hopkins CSSE github

covid-plot-data-from-jhu.py

#/usr/bin/python
import numpy as np
import matplotlib.pyplot as plt
import pandas as ps
import itertools as it
plt.ion()

data = ps.read_csv('time_series_covid19_confirmed_global.csv',parse_dates=True)
data_death = ps.read_csv('time_series_covid19_deaths_global.csv',parse_dates=True)
data_healt = ps.read_csv('time_series_covid19_recovered_global.csv',parse_dates=True)
countries_avail = data["Country/Region"]
date_available = data.keys()[4:]
filt = ["Canada","Germany","Korea*","Taiwan","US","Italy","France","Japan","Iran","UK","Spain","China"]
countries_avail = countries_avail[countries_avail.isin(filt)]
count = 1

#for country in it.cycle(set(countries_avail.values)):
for country in set(countries_avail.values):
    day_total = data[data["Country/Region"]==country][date_available].sum()
    day_death =  data_death[data_death["Country/Region"]==country][date_available].sum()
    day_healt = data_healt[data_healt["Country/Region"]==country][date_available].sum()
    day_still = day_total-day_healt-day_death

    plt.subplot(2,1,1)
    plt.title("{} COVID19 Growth".format(country))
    plt.grid(True)
    plt.xlim( [0,len(day_total.values)])
    plt.bar(range(len(day_total.values)),day_total.values,zorder=3,label="Cases")
    plt.bar(range(len(day_death.values)),day_death.values,zorder=3,label="Death")
    plt.bar(range(len(day_healt.values)),day_healt.values,bottom=day_death.values,zorder=3,label="Recovered")
    plt.legend(loc='upper left')
    #plt.tick_params(
    #    axis='x',
    #    which='both',
    #    labelbottom=False)
    plt.xticks(range(0,len(day_total.values),10),day_total.keys()[::10])

    #plt.xlabel("Day")
    plt.ylabel("Cases Total")
    plt.subplot(2,1,2)
    plt.grid(True)
    plt.xlim( [0,len(day_total.values)])
    plt.bar(range(len(day_total.values)),day_total.diff().values,zorder=3,label="Cases")
    plt.bar(range(len(day_death.values)),day_death.diff().values,zorder=3,label="Death")
    plt.bar(range(len(day_healt.values)),day_healt.diff().values,bottom=day_death.diff().values,zorder=3,label="Recovered")
    plt.tick_params(
                axis='x',
                which='both',
                labelbottom=False)
        
    plt.xlabel("Day")
    plt.ylabel("Change")
    plt.tight_layout(pad=1.2)
    plt.savefig("graph/{}.png".format(country))
    print(" Graph for {} ready".format(country))
    #plt.show()
    # plt.pause(6)
    plt.clf()