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- import csv
- from dataflows import Flow, load, unpivot, find_replace, set_type, dump_to_path
- import datapackage
-
- BASE_URL = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/'
- CONFIRMED = 'time_series_19-covid-Confirmed.csv'
- DEATH = 'time_series_19-covid-Deaths.csv'
- RECOVERED = 'time_series_19-covid-Recovered.csv'
-
- def to_normal_date(row):
- old_date = row['date']
- month, day, year = row['date'].split('-')
- day = f'0{day}' if len(day) == 1 else day
- month = f'0{month}' if len(month) == 1 else month
- row['date'] = '-'.join([day, month, year])
-
- unpivoting_fields = [
- { 'name': '([0-9]+\/[0-9]+\/[0-9]+)', 'keys': {'date': r'\1'} }
- ]
-
- extra_keys = [{'name': 'date', 'type': 'string'} ]
- extra_value = {'name': 'case', 'type': 'string'}
-
- for case in [CONFIRMED, DEATH, RECOVERED]:
- Flow(
- load(f'{BASE_URL}{case}'),
- unpivot(unpivoting_fields, extra_keys, extra_value),
- find_replace([{'name': 'date', 'patterns': [{'find': '/', 'replace': '-'}]}]),
- to_normal_date,
- set_type('date', type='date', format='%d-%m-%y'),
- set_type('case', type='number'),
- dump_to_path()
- ).results()[0]
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