import pandas as pd
from datetime import datetime as dt
import matplotlib.pyplot as plt
import numpy as np
# USEFUL FUNCTIONS




def getColumns(data_frame):
    for  col in data_frame:
        print(col)




def FormatedDate():
    formated_date = dt.today()
    print(formated_date)

FormatedDate()


# grabbing daily updated data CSWSEGISandData/COVID 19
df_confirmedUS= pd.read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv")
df_confirmedGlobal = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv')
df_deathsUS = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv')
df_deathsGlobal = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv')
df_recoveryGlobal = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv')
# daily updated data with UID
df_covid_19 = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/UID_ISO_FIPS_LookUp_Table.csv')

def get_todays_global_death_count():



    deaths  = df_deathsGlobal.iloc[:,[1,-1]].groupby('Country/Region').sum()


    #iloc test selects rows and columns from pandas data frames
    deaths_2 = df_deathsGlobal.iloc[:,[1,1]]
    print(deaths_2)
    todays_date = deaths.columns[0]
    print("\n Total number of Deaths as of... " ,todays_date )
    deaths = deaths.sort_values(by = todays_date, ascending = False)
    deaths = deaths[deaths[todays_date] > 0]


    #death test
    print(deaths, '\n  the death data frame boi '  )




    #death index retrun single array instead of an array of arrays
   # deaths_index_con = np.concatenate(deaths.index, axis = None)


    #death values retrun single array instead of an array of arrays
    deaths_values_con = np.concatenate(deaths.values , axis = None)

    total_global_deaths = deaths_values_con.sum()
    print("total global deaths .....  "  , total_global_deaths)


    print(deaths_values_con, '\n   this is the death values concatenated')


    #checking  values
    print(deaths.index , '\n death index printed boi ' )
    print(deaths.values , "\n death values printed son " )


    #type test
    print( ' \n deats.index datt type.... ', type(deaths.index))

    #plot

   # plt.xticks(ypos, deaths.index)
    #plt.bar( ypos,deaths_values_con)


get_todays_global_death_count()




#def get_todays_US_death_count():

 #   USDeaths  = df_confirmedUS.iloc[]