07-appendix.Rmd

`r if(knitr:::is_latex_output()) '\\appendix'`

`r if(!knitr:::is_latex_output()) '# (APPENDIX) Dodatek {-}'` 

# Program pobierający dzienne dane z witryny Worldometer

```{python, eval = FALSE}
    from datetime import datetime
    import requests
    from bs4 import BeautifulSoup
    import pandas as pd
    import numpy as np
    
    today = str(datetime.utcnow().date())
    URL = 'https://www.worldometers.info/coronavirus/'
    
    page = requests.get(URL)
    soup = BeautifulSoup(page.content, 'html.parser')
    table = soup.find('table', id='main_table_countries_today')
    header = table.find_all('th')
    header_names = [name.get_text().replace(u'\xa0', u' ').strip() for name in
    header]
    rows = table.find_all('tr', class_=None)[1:]
    df = pd.DataFrame(columns=header_names)
    
    final_out = []
    for row in rows:
        row_data = row.find_all('td')
        row_formatted = [tr.get_text().replace('\n', '') for tr in row_data]
        final_out.append(row_formatted)
        
        df = df.append(pd.DataFrame(final_out, columns=df.columns))
        df.insert(loc=0, column='Date', value=today)
        del df['#']
        
        df = df.replace(",", "", regex = True)
        df = df.replace(r'^\s*$', np.NaN, regex=True)
        df.columns = ["date", "country", "total_cases", "new_cases",
        "total_deaths", "new_deaths", "total_recovered", "new_recovered",
        "active_cases", "critical_cases", "total_cases_per_million",
        "total_deaths_per_million", "total_tests",
        "total_tests_per_million", "population", "continent",
        "one_case_per_x_people", "one_death_per_x_people",
        "one_test_per_x_people",
        "new_cases_per_million", "new_deaths_per_million",
        "active_cases_per_million"]
        df.to_csv(today + '.csv', index=False)
```