coronavirus: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset
In Covid19R/coronavirus: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset

Description Usage Format Details Source Examples

Daily summary of the Coronavirus (COVID-19) cases by state/province.

1	coronavirus

A data frame with 7 variables.

Province.State: Name of province/state, for countries where data is provided split across multiple provinces/states.
Country.Region: Name of country/region.
Lat: Latitude of center of geographic region, defined as either Country.Region or, if available, Province.State.
Long: Longitude of center of geographic region, defined as either Country.Region or, if available, Province.State.
date: Date in YYYY-MM-DD format.
cases: Number of cases on given date.
type: An indicator for the type of cases (confirmed, death, recovered).

The dataset contains the daily summary of Coronavirus cases (confirmed, death, and recovered), by state/province.

Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus website.

data(coronavirus)

require(dplyr)

# Get top confirmed cases by state
coronavirus %>%
  filter(type == "confirmed") %>%
  group_by(Country.Region) %>%
  summarise(total = sum(cases)) %>%
  arrange(-total) %>%
  head(20)

# Get the number of recovered cases in Mainland China by province
coronavirus %>%
  filter(type == "recovered", Country.Region == "Mainland China") %>%
  group_by(Province.State) %>%
  summarise(total = sum(cases)) %>%
  arrange(-total)