This Package helps users in knowing the top 4 countries with the highest number of coronavirus cases throughout the world. The top 4 countries as of October 2020 are:
in order. This package has a shiny app which gives the analysis and visualizations for these countries throughout the COVID19 pandemic. The data for these analyses and visualizations are taken from the COVID19 package on CRAN and a couple of datasets from Kaggle for individual state datasets for each state within the country.These datasets all contain the total number of cases, deaths and recovered over time.
NOTE!! : Please click on the country for the link to these datasets.
Some Examples on using the dataset within the package:
The table helps us find the total number of cases by country for each date.
corona %>% group_by(date, id) %>% summarise(total = sum(confirmed)) %>% tail(10) %>% knitr::kable() %>% kableExtra::kable_styling(bootstrap_options = "striped") #> `summarise()` regrouping output by 'date' (override with `.groups` argument)
| date | id | total |
|---|---|---|
| 2020-10-09 | IND | 6977102 |
| 2020-10-10 | RUS | 1278245 |
| 2020-10-11 | BRA | 5094979 |
| 2020-10-12 | USA | 7804199 |
| 2020-10-13 | IND | 7237288 |
| 2020-10-14 | RUS | 1332824 |
| 2020-10-15 | BRA | 5169386 |
| 2020-10-16 | USA | 8048865 |
| 2020-10-17 | IND | 7492735 |
| 2020-10-18 | RUS | 1390824 |
corona %>% group_by(date,id) %>% summarise(total = sum(confirmed)) %>% ggplot(aes(x = date, y = total,color =id))+ geom_line()+ facet_wrap(~id) + theme_minimal() #> `summarise()` regrouping output by 'date' (override with `.groups` argument)
corona %>% group_by(date,id) %>% summarise(school_closing = sum(school_closing)) %>% ggplot(aes(x = date, y = school_closing, color = id))+ geom_line()+ facet_wrap(~id)+ theme_minimal() #> `summarise()` regrouping output by 'date' (override with `.groups` argument)
The above examples are just a glimpse on how to use the datasets within this package, there are other datasets available for your exploration.