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'
}
