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added argument parsing

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Rory Healy 2021-04-10 15:16:53 +10:00
parent 4a04643bc7
commit 1a03366fb9
2 changed files with 2085 additions and 2078 deletions
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4146
owid-covid-data-2020-monthly.csv
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17
parta1.py
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@ -1,6 +1,11 @@
import pandas as pd
import argparse
# parse input arguments
parser = argparse.ArgumentParser()
parser.add_argument('path_to_csv', help = 'path to the csv file')
args = parser.parse_args()
all_covid_data = pd.read_csv('data/owid-covid-data.csv', encoding = 'ISO-8859-1')
# filter out data past 2020
@ -24,7 +29,7 @@ new_deaths_grouped = pd.DataFrame(new_deaths_grouped.to_records())
new_cases_grouped.sort_values(by = ['location', 'date'], inplace = True)
new_deaths_grouped.sort_values(by = ['location', 'date'], inplace = True)
# merge new_deaths and new_cases
# merge new_deaths_grouped and new_cases_grouped
aggregated_data = new_cases_grouped.merge(new_deaths_grouped, how = 'outer', left_on = ['location', 'date'], right_on = ['location', 'date'])
# filter out all entries that aren't at the end of the month
@ -41,12 +46,14 @@ total_deaths.date = total_deaths.date.dt.month
# merge total_deaths and total_cases into aggregated_data
aggregated_data = aggregated_data.merge(total_cases, how = 'outer', left_on = ['location', 'date'], right_on = ['location', 'date'])
aggregated_data = aggregated_data.merge(total_deaths, how = 'outer', left_on = ['location', 'date'], right_on = ['location', 'date'])
aggregated_data.rename(columns = {'date': 'month'}, inplace = True)
# compute case fatality rate for each month
aggregated_data['case_fatality_rate'] = (aggregated_data['new_deaths'] / aggregated_data['new_cases'])
aggregated_data = aggregated_data.reindex(columns = ['location', 'month', 'case_fatality_rate', 'total_cases', 'new_cases', 'total_deaths', 'new_deaths'])
# output results to csv and stdout
# format aggregated_data and output results
aggregated_data = aggregated_data.reindex(columns = ['location', 'date', 'case_fatality_rate', 'total_cases', 'new_cases', 'total_deaths', 'new_deaths'])
aggregated_data.rename(columns = {'date': 'month'}, inplace = True)
aggregated_data.set_index(['location', 'month'], inplace = True)
print(aggregated_data.head(5))
aggregated_data.to_csv('owid-covid-data-2020-monthly.csv')
aggregated_data.to_csv(args.path_to_csv)