In averissimo/r-analysis-covid19: COVID-19 Data Analysis

flog.info('### Summary of data ###')
flog.info('')
flog.info('  %s: %d', region(2), my.corona.original %>% filter(cases > 0) %>% pull(state) %>% unique %>% length)
flog.info('')
flog.info('           Cases: %s', sum((my.corona.original %>% filter(type == 'confirmed'))$cases) %>% format(big.mark = ','))
flog.info('          Deaths: %s', sum((my.corona.original %>% filter(type == 'death'))$cases)%>% format(big.mark = ','))
flog.info('')
flog.info('  Source of data: %s', last.date, source.by)

Main r region(2) in visualizations

The plots presented get very complex as more r region(2, TRUE) are added. I'm focusing mainly on Europe and comparing against Portugal and Germany (where I'm from vs. where I live)

flog.info('Looking only at the following %s: \n\n  %s' , region(2, TRUE), paste0(countries, collapse = ', '))

averissimo/r-analysis-covid19 documentation built on April 24, 2021, 11:01 a.m.