import pandas as pd
import numpy as np
data = pd.read_csv('owid-covid-data.csv')
df = data[['iso_code', 'date', 'total_cases']]
df['date']=pd.to_datetime(df['date'], format='%Y-%m-%d')
df.info()
iso = df.iso_code.unique()
df2 = pd.DataFrame(columns=['iso_code', 'date', 'total_cases'])
df3 = pd.DataFrame(columns=['iso_code', 'date', 'total_cases'])
for country in iso:
	country_v = df.loc[df['iso_code'] == country]
	months = country_v.set_index('date').groupby(pd.Grouper(freq='M')).max()
	i=0
	for index, month in months.iterrows():
		#df2.append(month)
		if i==months.shape[0]-1:
			df3 = df3.append({'iso_code': month['iso_code'], 'date': month.name, 'total_cases': month['total_cases']}, ignore_index=True)
		
		df2 = df2.append({'iso_code': month['iso_code'], 'date': month.name, 'total_cases': month['total_cases']}, ignore_index=True)
		i += 1
df2.to_csv('month-covid.csv', sep=',')
df3.to_csv('max-covid.csv', sep=',')