coronavirus {coronavirus}

The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset

Description

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

Usage

coronavirus

Format

A data frame with 7 variables.

date

Date in YYYY-MM-DD format.

province

Name of province/state, for countries where data is provided split across multiple provinces/states.

country

Name of country/region.

lat

Latitude of center of geographic region, defined as either country or, if available, province.

long

Longitude of center of geographic region, defined as either country or, if available, province.

type

An indicator for the type of cases (confirmed, death, recovered).

cases

Number of cases on given date.

uid

Country code

iso2

Officially assigned country code identifiers with two-letter

iso3

Officially assigned country code identifiers with three-letter

code3

UN country code

combined_key

Country and province (if applicable)

population

Country or province population

continent_name

Continent name

continent_code

Continent code

Details

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

Source

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

Examples

data(coronavirus)

require(dplyr)

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

# Get the number of recovered cases in China by province
coronavirus %>%
  filter(type == "recovered", country == "China") %>%
  group_by(province) %>%
  summarise(total = sum(cases)) %>%
  arrange(-total)