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33 lines
1.2 KiB

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]