def parseAdministered(file, vacc_data):
idxGeoRegion = 0
idxDate = 0
idxSumTotal = 0
idxPer100PersonsTotal = 0
idxType = 0
csvreader = csv.reader(open(file, "r"), delimiter=',', quotechar='"')
for row in csvreader:
if row[0] == "date": # skip header line
idxGeoRegion, idxDate, idxSumTotal, idxPer100PersonsTotal, idxType = extractIdx(
row, 'geoRegion', 'date', 'sumTotal', 'per100PersonsTotal',
'type')
continue
# print(', '.join(row))
date = row[idxDate]
canton = row[idxGeoRegion]
if canton in ["all", "neighboring_chfl", "unknown"]:
continue
total = row[idxSumTotal]
per100 = row[idxPer100PersonsTotal]
dtype = row[idxType]
if date not in vacc_data:
vacc_data[date] = {}
if canton not in vacc_data[date]:
vacc_data[date][canton] = {}
if dtype == "COVID19VaccDosesAdministered":
vacc_data[date][canton]["administeredTotal"] = total
vacc_data[date][canton]["administeredPer100"] = per100
return vacc_data
def parse_hosp(file, data):
idxGeoRegion = 0
idxDate = 0
idxCurrIcu = 0
idxCurrHosp = 0
csvreader = csv.reader(open(file, "r"), delimiter=',', quotechar='"')
for row in csvreader:
if row[0] == "date":
idxGeoRegion, idxDate, idxCurrIcu, idxCurrHosp = extractIdx(
row, 'geoRegion', 'date', 'ICU_Covid19Patients',
'Total_Covid19Patients')
continue
canton = row[idxGeoRegion]
date = row[idxDate]
currHosp = row[idxCurrHosp]
currIcu = row[idxCurrIcu]
if canton not in data:
data[canton] = {}
if date not in data[canton]:
data[canton][date] = {
"total": 0,
"current_hosp": 0,
"current_icu": 0,
"death": 0
}
data[canton][date]["current_hosp"] = currHosp
data[canton][date]["current_icu"] = currIcu
return data
def parse_timestamps(file, data):
idxVariant = 0
idxVersion = 0
csvreader = csv.reader(open(file, "r"), delimiter=',', quotechar='"')
for row in csvreader:
if row[0] == "type":
idxVariant, idxVersion = extractIdx(row, 'type_variant', 'version')
continue
variant = row[idxVariant][10:]
timestamp = row[idxVersion]
data[variant] = timestamp
return data
def parsePersons(file, data):
idxGeoRegion = 0
idxPop = 0
idxAgeGroup = 0
csvreader = csv.reader(open(file, "r"), delimiter=',', quotechar='"')
for row in csvreader:
if row[0] == "date": # skip header line
idxGeoRegion, idxPop, idxAgeGroup = extractIdx(row, 'geoRegion', 'pop', 'age_group')
continue
# print(', '.join(row))
if (row[idxAgeGroup] != 'total_population'):
continue
if not row[idxPop].isnumeric():
continue
canton = row[idxGeoRegion]
pop = row[idxPop]
data[canton] = pop
return data
def parse_death(file, data):
idxGeoRegion = 0
idxDatum = 0
idxSumTotal = 0
csvreader = csv.reader(open(file, "r"), delimiter=',', quotechar='"')
for row in csvreader:
if row[0] == "geoRegion":
idxGeoRegion, idxDatum, idxSumTotal = extractIdx(
row, 'geoRegion', 'datum', 'sumTotal')
continue
canton = row[idxGeoRegion]
date = row[idxDatum]
total = row[idxSumTotal]
if canton not in data:
data[canton] = {}
if date not in data[canton]:
data[canton][date] = {
"total": 0,
"current_hosp": 0,
"current_icu": 0,
"death": 0
}
data[canton][date]["death"] = total
return data
def parseVaccPersons(file, vacc_data):
idxGeoRegion = 0
idxDate = 0
idxSumTotal = 0
idxPer100PersonsTotal = 0
idxType = 0
csvreader = csv.reader(open(file, "r"), delimiter=',', quotechar='"')
for row in csvreader:
if row[0] == "date": # skip header line
idxGeoRegion, idxDate, idxSumTotal, idxPer100PersonsTotal, idxType, idxAgeGroup = extractIdx(
row, 'geoRegion', 'date', 'sumTotal', 'per100PersonsTotal',
'type', 'age_group')
continue
# print(', '.join(row))
date = row[idxDate]
canton = row[idxGeoRegion]
if canton in ["all", "neighboring_chfl", "unknown"]:
continue
total = row[idxSumTotal]
per100 = row[idxPer100PersonsTotal]
dtype = row[idxType]
ageGroup = row[idxAgeGroup]
if ageGroup != "total_population":
continue
if date not in vacc_data:
vacc_data[date] = {}
if canton not in vacc_data[date]:
vacc_data[date][canton] = {}
if dtype == "COVID19FullyVaccPersons":
vacc_data[date][canton]["fullyVaccTotal"] = total
vacc_data[date][canton]["fullyVaccPer100"] = per100
return vacc_data
def parseVaccPersons(file, vacc_data_total, vacc_data_twelveplus):
idxGeoRegion = 0
idxDate = 0
idxSumTotal = 0
idxPer100PersonsTotal = 0
idxType = 0
csvreader = csv.reader(open(file, "r"), delimiter=',', quotechar='"')
for row in csvreader:
if row[0] == "date": # skip header line
idxGeoRegion, idxDate, idxSumTotal, idxPer100PersonsTotal, idxType, idxAgeGroup, idxPop = extractIdx(
row, 'geoRegion', 'date', 'sumTotal', 'per100PersonsTotal',
'type', 'age_group', 'pop')
continue
# print(', '.join(row))
date = row[idxDate]
canton = row[idxGeoRegion]
if canton in ["all", "neighboring_chfl", "unknown"]:
continue
total = row[idxSumTotal]
per100 = row[idxPer100PersonsTotal]
dtype = row[idxType]
ageGroup = row[idxAgeGroup]
pop = row[idxPop]
if ageGroup == "total_population":
vacc_data_total = getVaccData(vacc_data_total, date, canton, pop,
dtype, total, per100)
elif ageGroup == "12+":
vacc_data_twelveplus = getVaccData(vacc_data_twelveplus, date,
canton, pop, dtype, total,
per100)
return vacc_data_total, vacc_data_twelveplus