case_fatality_rate added
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3 changed files with 2084 additions and 74006 deletions
73994
output.csv
73994
output.csv
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2073
owid-covid-data-2020-monthly.csv
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2073
owid-covid-data-2020-monthly.csv
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23
parta1.py
23
parta1.py
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@ -24,13 +24,8 @@ new_deaths_grouped = pd.DataFrame(new_deaths_grouped.to_records())
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new_cases_grouped.sort_values(by = ['location', 'date'], inplace = True)
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new_deaths_grouped.sort_values(by = ['location', 'date'], inplace = True)
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# rename columns
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new_cases_grouped.rename(columns = {'date': 'month'}, inplace = True)
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new_deaths_grouped.rename(columns = {'date': 'month'}, inplace = True)
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# merge new_deaths and new_cases
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new_cases_grouped = new_cases_grouped.reindex(columns = ['location', 'month', 'new_cases'])
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aggregated_data = new_cases_grouped.merge(new_deaths_grouped, how = 'outer', left_on = ['location', 'month'], right_on = ['location', 'month'])
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aggregated_data = new_cases_grouped.merge(new_deaths_grouped, how = 'outer', left_on = ['location', 'date'], right_on = ['location', 'date'])
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# filter out all entries that aren't at the end of the month
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all_covid_data['end_of_month'] = pd.to_datetime(all_covid_data['date']).dt.is_month_end
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@ -39,15 +34,19 @@ all_covid_data = all_covid_data.loc[all_covid_data.end_of_month, :]
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# extract monthly total cases and total deaths
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total_cases = all_covid_data.loc[:, ['location', 'date', 'total_cases']]
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total_cases.date = total_cases.date.dt.month
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total_cases.rename(columns = {'date': 'month'}, inplace = True)
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total_deaths = all_covid_data.loc[:, ['location', 'date', 'total_deaths']]
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total_deaths.date = total_deaths.date.dt.month
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total_deaths.rename(columns = {'date': 'month'}, inplace = True)
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# merge total_deaths and total_cases into aggregated_data
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aggregated_data = aggregated_data.merge(total_cases, how = 'outer', left_on = ['location', 'month'], right_on = ['location', 'month'])
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aggregated_data = aggregated_data.merge(total_deaths, how = 'outer', left_on = ['location', 'month'], right_on = ['location', 'month'])
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aggregated_data = aggregated_data.reindex(columns = ['location', 'month', 'total_cases', 'new_cases', 'total_deaths', 'new_deaths'])
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aggregated_data = aggregated_data.merge(total_cases, how = 'outer', left_on = ['location', 'date'], right_on = ['location', 'date'])
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aggregated_data = aggregated_data.merge(total_deaths, how = 'outer', left_on = ['location', 'date'], right_on = ['location', 'date'])
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aggregated_data.rename(columns = {'date': 'month'}, inplace = True)
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print(aggregated_data.head(25))
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# compute case fatality rate for each month
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aggregated_data['case_fatality_rate'] = (aggregated_data['new_deaths'] / aggregated_data['new_cases'])
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aggregated_data = aggregated_data.reindex(columns = ['location', 'month', 'case_fatality_rate', 'total_cases', 'new_cases', 'total_deaths', 'new_deaths'])
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# output results to csv and stdout
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print(aggregated_data.head(5))
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aggregated_data.to_csv('owid-covid-data-2020-monthly.csv')
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