import numpy as np import pandas as pd import matplotlib.pyplot as plt import covid import urllib from scipy import signal import datetime import os #%% Get the data datapath = '.\\data' csv_file_pop = os.path.join(datapath, 'Population-Data-WI.csv') # covid.download_pop_data_wi(csv_file_pop) popdata = covid.read_pop_data_wi(csv_file_pop) # covid data widata = covid.read_covid_data_wi('state') #%% By Test # manually downloaded file - positives and tests test_file = "data\\By_Test_Data_data_2020-10-19.csv" test = pd.read_csv(test_file) test = test[test['Measure Names']=='Positive tests'] col_rename = {'Day of displaydateonly': 'Date', 'Positives': 'Positives', 'Totals': 'Tests' } test = test[col_rename.keys()]
# wi_pop = age_total['Population'].sum() total_immune_age = (age_total['Immune %'] / 100 * age_total['Population']).sum() / wi_pop total_vax = age_total['Vaccinated #'].sum() / wi_pop total_infected = age_total['Cases'].sum() * infection_factor / wi_pop total_immune_naive = total_vax + (1 - total_vax) * total_infected #%% Trying by county? county = covid.read_covid_data_wi('county') county = county[county.Date == pd.to_datetime('2021-05-20')] county = county.set_index('NAME') # population data popdata = covid.read_pop_data_wi('data\\Population-Data-WI.csv') county['Population'] = popdata # vax data url = 'https://bi.wisconsin.gov/t/DHS/views/VaccinesAdministeredtoWIResidents_16212677845310/VaccinatedWisconsin-County?:embed_code_version=3&:embed=y&:loadOrderID=1&:display_spinner=no&:showAppBanner=false&:display_count=n&:showVizHome=n&:origin=viz_share_link' ts = loads_with_retries(ts, url, 3) vax_dash = ts.getWorkbook() vax_county = vax_dash.worksheets[0].data col_rename = { 'Region-alias': 'Region', 'County-alias': 'County', 'Measure Names-alias': 'Measure', 'Measure Values-alias': 'Value' }