add metadata from new columns and make every module fit to use this. add stringence of local measures as background of plot, add vaccination status to plots, mute unreasonable warnings
This commit is contained in:
fordprefect
121
coronavis.py
121
coronavis.py
@@ -20,11 +20,46 @@ plots = ["basics", "death_per_case",
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"doubling_time",
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"all_countries",
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]
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metadata_fields = [
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"iso_code",
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"continent",
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"location",
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"population",
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"population_density",
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"median_age",
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"aged_65_older",
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"aged_70_older",
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"gdp_per_capita",
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"extreme_poverty",
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"cardiovasc_death_rate",
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"diabetes_prevalence",
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"female_smokers",
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"male_smokers",
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"handwashing_facilities",
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"hospital_beds_per_thousand",
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"life_expectancy",
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"human_development_index",
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]
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### manual data
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# population: sourced ECDC data
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from population_repository import pop
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###
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def toint(a):
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try:
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return int(a)
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except:
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return np.nan
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def tofloat(a):
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try:
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return float(a)
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except:
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return np.nan
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def addmeta(field, value):
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pass
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def get_data():
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"""fetch data from remote, cache locally and reorganize internal data
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not beautiful (at all), but effective!!"""
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@@ -55,6 +90,7 @@ def get_data():
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# processing
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data = {}
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metadata = {}
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with open(datafile, "r") as f:
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reader = csv.reader(f)
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for row in reader:
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@@ -64,80 +100,61 @@ def get_data():
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date,location,new_cases,new_deaths,total_cases,total_deaths,weekly_cases,weekly_deaths,biweekly_cases,biweekly_deaths = row
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elif len(row) == 50:
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iso_code,continent,location,date,total_cases,new_cases,new_cases_smoothed,total_deaths,new_deaths,new_deaths_smoothed,total_cases_per_million,new_cases_per_million,new_cases_smoothed_per_million,total_deaths_per_million,new_deaths_per_million,new_deaths_smoothed_per_million,reproduction_rate,icu_patients,icu_patients_per_million,hosp_patients,hosp_patients_per_million,weekly_icu_admissions,weekly_icu_admissions_per_million,weekly_hosp_admissions,weekly_hosp_admissions_per_million,new_tests,total_tests,total_tests_per_thousand,new_tests_per_thousand,new_tests_smoothed,new_tests_smoothed_per_thousand,positive_rate,tests_per_case,tests_units,stringency_index,population,population_density,median_age,aged_65_older,aged_70_older,gdp_per_capita,extreme_poverty,cardiovasc_death_rate,diabetes_prevalence,female_smokers,male_smokers,handwashing_facilities,hospital_beds_per_thousand,life_expectancy,human_development_index = row
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elif len(row) == 52:
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iso_code,continent,location,date,total_cases,new_cases,new_cases_smoothed,total_deaths,new_deaths,new_deaths_smoothed,total_cases_per_million,new_cases_per_million,new_cases_smoothed_per_million,total_deaths_per_million,new_deaths_per_million,new_deaths_smoothed_per_million,reproduction_rate,icu_patients,icu_patients_per_million,hosp_patients,hosp_patients_per_million,weekly_icu_admissions,weekly_icu_admissions_per_million,weekly_hosp_admissions,weekly_hosp_admissions_per_million,new_tests,total_tests,total_tests_per_thousand,new_tests_per_thousand,new_tests_smoothed,new_tests_smoothed_per_thousand,positive_rate,tests_per_case,tests_units,total_vaccinations,total_vaccinations_per_hundred,stringency_index,population,population_density,median_age,aged_65_older,aged_70_older,gdp_per_capita,extreme_poverty,cardiovasc_death_rate,diabetes_prevalence,female_smokers,male_smokers,handwashing_facilities,hospital_beds_per_thousand,life_expectancy,human_development_index = row
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else:
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print(f"WARNING! Table format changed, new header:\n{row})")
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exit(1)
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# break loop if header
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if location=="location":
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# table header
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header = row
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continue
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# cast to num type
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if isinstance(total_cases, str):
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if total_cases in ('', ' ', '0.0'):
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total_cases = 0
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try:
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total_cases = int(total_cases)
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except:
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try:
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total_cases = float(total_cases)
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except:
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print("tc failed")
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if isinstance(new_cases, str):
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if new_cases in ('', ' ', '0.0'):
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new_cases = 0
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try:
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new_cases = int(new_cases)
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except:
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try:
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new_cases = float(new_cases)
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except:
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print("nc failed")
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if isinstance(new_deaths, str):
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if new_deaths in ('', ' ', '0.0'):
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new_deaths = 0
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try:
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new_deaths = int(new_deaths)
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except:
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try:
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new_deaths = float(new_deaths)
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except:
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print("nd failed")
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if isinstance(total_deaths, str):
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if total_deaths in ('', ' ', '0.0'):
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total_deaths = 0
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try:
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total_deaths = int(total_deaths)
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except:
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try:
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total_deaths = float(total_deaths)
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except:
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print("td failed")
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total_cases = tofloat(total_cases)
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new_cases = tofloat(new_cases)
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total_deaths = tofloat(total_deaths)
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new_deaths = tofloat(new_deaths)
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total_vaccinations = tofloat(total_vaccinations)
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stringency_index = tofloat(stringency_index)
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if location not in data:
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data[location] = []
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metadata[location] = {}
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year, month, day = date.split("-")
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def toint(a):
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try:
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return int(a)
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except:
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return np.nan
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data[location].append([datetime.date(int(year), int(month), int(day)), new_cases, new_deaths, total_cases, total_deaths])
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data[location].append([datetime.date(int(year), int(month), int(day)), new_cases, new_deaths, total_cases, total_deaths, total_vaccinations, stringency_index])
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# catch all data fields
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#dfields = {field: row[n] for n, field in enumerate(header)}
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# add metadata
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for n, field in enumerate(header):
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if field in metadata_fields:
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if field not in metadata[location]:
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metadata[location][field] = row[n]
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else:
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if metadata[location][field] != row[n]:
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print(f"{location}: {field} seems not to be a constant ({metadata[location][field]} vs {row[n]})")
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# reorganize data
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data2 = {}
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for loc in data:
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time = []
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new_cases, new_deaths, total_cases, total_deaths = [], [], [], []
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new_cases, new_deaths, total_cases, total_deaths, total_vaccinations, stringency_index = [], [], [], [], [], []
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for entry in data[loc]:
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t_, new_cases_, new_deaths_, total_cases_, total_deaths_ = entry
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t_, new_cases_, new_deaths_, total_cases_, total_deaths_, total_vaccinations_, stringency_index_ = entry
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time.append(t_)
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new_cases.append(toint(new_cases_))
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new_deaths.append(toint(new_deaths_))
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total_cases.append(toint(total_cases_))
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total_deaths.append(toint(total_deaths_))
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data2[loc] = [time, new_cases, new_deaths, total_cases, total_deaths]
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return data2
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total_vaccinations.append(toint(total_vaccinations_))
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stringency_index.append(toint(stringency_index_))
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data2[loc] = {'time': time, 'new_cases': new_cases, 'new_deaths': new_deaths, 'total_cases': total_cases, 'total_deaths': total_deaths, 'total_vaccinations': total_vaccinations, "stringency_index": stringency_index}
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return data2, metadata
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data = get_data()
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data, metadata = get_data()
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for plot in plots:
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i = importlib.import_module(plot)
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i.plot(data, countries, pop)
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i.plot(data, countries, pop, metadata=metadata)
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