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from dataflows import Flow, load, unpivot, find_replace, set_type, dump_to_path, update_package, update_resource, update_schema, join, join_with_self, add_computed_field, delete_fields, checkpoint, duplicate, filter_rows
BASE_URL = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/'
CONFIRMED = 'time_series_covid19_confirmed_global.csv'
DEATH = 'time_series_covid19_deaths_global.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': 'number'}
def is_key_country(row):
key_countries = ['Chine', 'US', 'United Kingdom', 'Italy', 'France', 'Germany']
return row['Country'] in key_countries
Flow(
load(f'{BASE_URL}{CONFIRMED}'),
load(f'{BASE_URL}{RECOVERED}'),
load(f'{BASE_URL}{DEATH}'),
checkpoint('load_data'),
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', resources=None),
set_type('Case', type='number', resources=None),
join(
source_name='time_series_covid19_confirmed_global',
source_key=['Province/State', 'Country/Region', 'Date'],
source_delete=True,
target_name='time_series_covid19_deaths_global',
target_key=['Province/State', 'Country/Region', 'Date'],
fields=dict(Confirmed={
'name': 'Case',
'aggregate': 'first'
})
),
join(
source_name='time_series_19-covid-Recovered',
source_key=['Province/State', 'Country/Region', 'Date'],
source_delete=True,
target_name='time_series_covid19_deaths_global',
target_key=['Province/State', 'Country/Region', 'Date'],
fields=dict(Recovered={
'name': 'Case',
'aggregate': 'first'
})
),
add_computed_field(
target={'name': 'Deaths', 'type': 'number'},
operation='format',
with_='{Case}'
),
delete_fields(['Case']),
update_resource('time_series_covid19_deaths_global', name='time-series-19-covid-combined', path='data/time-series-19-covid-combined.csv'),
update_schema('time-series-19-covid-combined', missingValues=['None', ''], fields=[
{
"format": "%Y-%m-%d",
"name": "Date",
"type": "date"
},
{
"format": "default",
"name": "Country/Region",
"type": "string"
},
{
"format": "default",
"name": "Province/State",
"type": "string"
},
{
"decimalChar": ".",
"format": "default",
"groupChar": "",
"name": "Lat",
"type": "number"
},
{
"decimalChar": ".",
"format": "default",
"groupChar": "",
"name": "Long",
"type": "number"
},
{
"format": "default",
"groupChar": "",
"name": "Confirmed",
"title": "Cumulative total confirmed cases to date",
"type": "integer"
},
{
"format": "default",
"groupChar": "",
"name": "Recovered",
"title": "Cumulative total recovered cases to date",
"type": "integer"
},
{
"format": "default",
"groupChar": "",
"name": "Deaths",
"title": "Cumulative total deaths to date",
"type": "integer"
}
]),
checkpoint('processed_data'),
# Duplicate the stream to create aggregated data
duplicate(
source='time-series-19-covid-combined',
target_name='worldwide-aggregated',
target_path='data/worldwide-aggregated.csv'
),
join_with_self(
resource_name='worldwide-aggregated',
join_key=['Date'],
fields=dict(
Date={
'name': 'Date'
},
Confirmed={
'name': 'Confirmed',
'aggregate': 'sum'
},
Recovered={
'name': 'Recovered',
'aggregate': 'sum'
},
Deaths={
'name': 'Deaths',
'aggregate': 'sum'
}
)
),
update_schema('worldwide-aggregated', missingValues=['None', ''], fields=[
{
"format": "%Y-%m-%d",
"name": "Date",
"type": "date"
},
{
"format": "default",
"groupChar": "",
"name": "Confirmed",
"title": "Cumulative total confirmed cases to date",
"type": "integer"
},
{
"format": "default",
"groupChar": "",
"name": "Recovered",
"title": "Cumulative total recovered cases to date",
"type": "integer"
},
{
"format": "default",
"groupChar": "",
"name": "Deaths",
"title": "Cumulative total deaths to date",
"type": "integer"
}
]),
checkpoint('processed_worldwide_data'),
# Create another resource with countries aggregated
duplicate(
source='time-series-19-covid-combined',
target_name='countries-aggregated',
target_path='data/countries-aggregated.csv'
),
join_with_self(
resource_name='countries-aggregated',
join_key=['Date', 'Country/Region'],
fields=dict(
Date={
'name': 'Date'
},
Country={
'name': 'Country/Region'
},
Confirmed={
'name': 'Confirmed',
'aggregate': 'sum'
},
Recovered={
'name': 'Recovered',
'aggregate': 'sum'
},
Deaths={
'name': 'Deaths',
'aggregate': 'sum'
}
)
),
update_schema('countries-aggregated', missingValues=['None', ''], fields=[
{
"format": "%Y-%m-%d",
"name": "Date",
"type": "date"
},
{
"format": "default",
"name": "Country",
"type": "string"
},
{
"format": "default",
"groupChar": "",
"name": "Confirmed",
"title": "Cumulative total confirmed cases to date",
"type": "integer"
},
{
"format": "default",
"groupChar": "",
"name": "Recovered",
"title": "Cumulative total recovered cases to date",
"type": "integer"
},
{
"format": "default",
"groupChar": "",
"name": "Deaths",
"title": "Cumulative total deaths to date",
"type": "integer"
}
]),
checkpoint('processed_country_data'),
# Prepare data package (name, title) and add views
update_package(
name='covid-19',
title='Novel Coronavirus 2019',
views=[
{
"title": "Total world to date",
"resources": ["worldwide-aggregated"],
"specType": "simple",
"spec": {
"group": "Date",
"series": ["Confirmed", "Recovered", "Deaths"],
"type": "line"
}
}
]
),
dump_to_path()
).results()[0]