Import Data

data.py

giturl_confirmed = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv'
giturl_deaths = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Deaths.csv'
giturl_recovered = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Recovered.csv'

casestr='Deaths'   #'Confirmed' #'Recovered', 'Deaths'
chosen_plotmodel = 'Logistic'  #'Logistc'

if casestr=='Confirmed':
    curl = giturl_confirmed
elif casestr=='Deaths':
    curl = giturl_deaths
elif casestr=='Recovered':
    curl = giturl_recovered
    
corona_cases_df=pd.read_csv(curl, index_col=[0,1,2,3])  
#   use first four columns as multiindex

corona_cases_df.columns.values
>>> 
array(['1/22/20', '1/23/20', '1/24/20', '1/25/20', '1/26/20', '1/27/20',
       '1/28/20', '1/29/20', '1/30/20', '1/31/20', '2/1/20', '2/2/20',
       '2/3/20', '2/4/20', '2/5/20', '2/6/20', '2/7/20', '2/8/20',
       '2/9/20', '2/10/20', '2/11/20', '2/12/20', '2/13/20', '2/14/20',
       '2/15/20', '2/16/20', '2/17/20', '2/18/20', '2/19/20', '2/20/20',
       '2/21/20', '2/22/20', '2/23/20', '2/24/20', '2/25/20', '2/26/20',
       '2/27/20', '2/28/20', '2/29/20', '3/1/20', '3/2/20', '3/3/20',
       '3/4/20', '3/5/20', '3/6/20', '3/7/20', '3/8/20', '3/9/20',
       '3/10/20', '3/11/20', '3/12/20', '3/13/20', '3/14/20', '3/15/20',
       '3/16/20'], dtype=object)