'Q_Symptoms','Q_Voluntary','Q_Personal','Q_General','Left_Quarantine'] ''' # Generate the area data print('Generating the Area data') wiki_scraper = covid19_WebScrapes.Wiki_Scrape() county_areas = wiki_scraper.Scrape_Counties() County_Areas = pd.DataFrame( county_areas, columns=['State', 'County_FIPS', 'County', 'Area (sqmi)']) County_Areas['Area (sqmi)'] = County_Areas['Area (sqmi)'].apply( lambda x: str(x).replace(',', '')) County_Areas['Area (sqmi)'] = County_Areas['Area (sqmi)'].astype(float) # Generate the Google Mobility time series data print('Generating the Google Mobility Data') google = covid19_WebScrapes.Alphabet_Scrape_V2() google_df = google.get_Data(country='United States', country_only=False, state_only=False) #pulls county info only # Generate the Orders Data print('Generating the Orders Data') orders = covid19_WebScrapes.OrdersScrape() orders_df = orders.getzip() # Clean and merge data. print('Cleaning all data') data_cleaner = covid19_WebScrapes.Clean_Data( './manually_pulled/FIPS_Codes_USDA.csv', './manually_pulled/new_state_mapping.txt') area_data_cleaned = data_cleaner.Clean_Area_Data(County_Areas)