new header size, add total boosters to available data dict
This commit is contained in:
14
coronavis.py
14
coronavis.py
@@ -91,7 +91,7 @@ def get_data():
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## file archiving: include error log just in case…
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try:
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subprocess.run(["/usr/bin/cp", f"../{date}-full-data.csv", "data.csv"], cwd="/srv/http/dukun.de/corona/data/git")
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subprocess.run(["/usr/bin/git", "commit", "-a", f"-m'{date}'"], cwd="/srv/http/dukun.de/corona/data/git")
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subprocess.run(["/usr/bin/git", "commit", "-a", f"-m {date}"], cwd="/srv/http/dukun.de/corona/data/git")
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subprocess.run(["/usr/bin/git", "push"], cwd="/srv/http/dukun.de/corona/data/git")
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except Exception as e:
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print(f"File archiving failed with {e} - need for debugging here…")
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@@ -125,6 +125,10 @@ def get_data():
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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, total_tests, new_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, people_vaccinated, people_fully_vaccinated, new_vaccinations, new_vaccinations_smoothed, total_vaccinations_per_hundred, people_vaccinated_per_hundred, people_fully_vaccinated_per_hundred, new_vaccinations_smoothed_per_million, 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) == 60:
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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, people_vaccinated, people_fully_vaccinated, new_vaccinations, new_vaccinations_smoothed, total_vaccinations_per_hundred, people_vaccinated_per_hundred, people_fully_vaccinated_per_hundred, new_vaccinations_smoothed_per_million, 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, excess_mortality = row
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elif len(row) == 62:
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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, people_vaccinated, people_fully_vaccinated, total_boosters, new_vaccinations, new_vaccinations_smoothed, total_vaccinations_per_hundred, people_vaccinated_per_hundred, people_fully_vaccinated_per_hundred, total_boosters_per_hundred, new_vaccinations_smoothed_per_million, 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, excess_mortality = row
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elif len(row) == 63:
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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, people_vaccinated, people_fully_vaccinated, total_boosters, new_vaccinations, new_vaccinations_smoothed, total_vaccinations_per_hundred, people_vaccinated_per_hundred, people_fully_vaccinated_per_hundred, total_boosters_per_hundred, new_vaccinations_smoothed_per_million, 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, excess_mortality_cumulative, excess_mortality = row
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else:
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print(f"WARNING! Table format changed, length now {len(row)}, new header:\n{row})")
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exit(1)
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@@ -153,6 +157,7 @@ def get_data():
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tests_per_case = tofloat(tests_per_case)
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new_vaccinations = tofloat(new_vaccinations)
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tests_units = tests_units
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total_boosters = tofloat(total_boosters)
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if location not in data:
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data[location] = []
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@@ -164,7 +169,7 @@ def get_data():
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stringency_index, reproduction_rate, icu_patients, hosp_patients,
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weekly_icu_admissions, weekly_hosp_admissions, new_tests,
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total_tests, positive_rate, tests_per_case, tests_units,
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new_vaccinations, people_fully_vaccinated]
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new_vaccinations, people_fully_vaccinated, total_boosters]
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)
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@@ -210,8 +215,9 @@ def get_data():
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tests_units = []
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new_vaccinations = []
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people_fully_vaccinated = []
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total_boosters = []
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for entry in data[loc]:
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t_, new_cases_, new_deaths_, total_cases_, total_deaths_, total_vaccinations_, stringency_index_, reproduction_rate_, icu_patients_, hosp_patients_, weekly_icu_admissions_, weekly_hosp_admissions_, new_tests_, total_tests_, positive_rate_, tests_per_case_, tests_units_, new_vaccinations_, people_fully_vaccinated_ = entry
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t_, new_cases_, new_deaths_, total_cases_, total_deaths_, total_vaccinations_, stringency_index_, reproduction_rate_, icu_patients_, hosp_patients_, weekly_icu_admissions_, weekly_hosp_admissions_, new_tests_, total_tests_, positive_rate_, tests_per_case_, tests_units_, new_vaccinations_, people_fully_vaccinated_, total_boosters_ = entry
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time.append(t_)
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new_cases.append(toint(new_cases_))
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@@ -232,6 +238,7 @@ def get_data():
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new_vaccinations.append(toint(new_vaccinations_))
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tests_units.append(tests_units_)
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people_fully_vaccinated.append(people_fully_vaccinated_)
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total_boosters.append(total_boosters_)
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### data tweaking and fixing goes here
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@@ -268,6 +275,7 @@ def get_data():
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'tests_units': tests_units,
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'new_vaccinations': new_vaccinations,
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'people_fully_vaccinated': people_fully_vaccinated,
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'total_boosters': total_boosters,
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}
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# add vaccine info to metadata
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if loc in vaccines_country_dict:
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