combine.py

#We will create an aggregated dataset by aggreagting the required columns using previous function.
summary_cols = ['people_vaccinated', 
                     'people_vaccinated_per_hundred', 
                     'people_fully_vaccinated', 
                     'people_fully_vaccinated_per_hundred', 
                     'total_vaccinations_per_hundred', 
                     'total_vaccinations']

summary = summary_df.set_index("country")
vaccines = vaccine_df[['country', 'vaccines']].drop_duplicates().set_index('country')
summary = summary.join(vaccines)

for col in summary_cols:   
   summary = summary.join(aggregate(vaccine_df, col))

#Two aditional columns for better understanding
summary['percentage_vaccinated'] = summary.people_vaccinated / summary.population * 100
summary['tested_positive'] = summary.total_confirmed / summary.total_tests * 100